مراجع:
Books_v1_01
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Books_v1_01')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 6106719 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
ساعات_ v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Watches_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 960872 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Personal_Care_Appliance_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Personal_Care_Appliances_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 85981 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Mobile_Electronics_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Mobile_Electronics_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 104975 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Digital_Video_Games_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Digital_Video_Games_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 145431 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Digital_Software_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Digital_Software_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 102084 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
الرئيسية_التطبيقات_ v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Major_Appliances_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 96901 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Gift_Card_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Gift_Card_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 149086 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Video_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Video_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 380604 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
الأمتعة_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Luggage_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 348657 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
برنامج_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Software_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 341931 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Video_Games_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Video_Games_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 1785997 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
أثاث_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Furniture_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 792113 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
الآلات الموسيقية_ v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Musical_Instruments_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 904765 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Digital_Music_Purchase_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Digital_Music_Purchase_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 1688884 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Books_v1_02
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Books_v1_02')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 3105520 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
الصفحة الرئيسية_الترفيه_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Home_Entertainment_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 705889 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
بقالة_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Grocery_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 2402458 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Outdoors_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Outdoors_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 2302401 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Pet_Products_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Pet_Products_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 2643619 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Video_DVD_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Video_DVD_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 5069140 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
ملابس_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Apparel_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 5906333 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
PC_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/PC_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 6908554 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Tools_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Tools_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 1741100 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
مجوهرات_ v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Jewelry_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 1767753 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Baby_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Baby_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 1752932 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Home_Improvement_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Home_Improvement_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 2634781 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Camera_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Camera_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 1801974 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Lawn_and_Garden_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Lawn_and_Garden_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 2557288 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Office_Products_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Office_Products_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 2642434 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Electronics_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Electronics_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 3093869 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
السيارات_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Automotive_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 3514942 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Digital_Video_Download_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Digital_Video_Download_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 4057147 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Mobile_Apps_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Mobile_Apps_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 5033376 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
أحذية_ v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Shoes_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 4366916 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
اللعب_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Toys_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 4864249 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
الرياضة v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Sports_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 4850360 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
مطبخ_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Kitchen_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 4880466 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Beauty_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Beauty_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 5115666 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Music_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Music_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 4751577 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
الصحة_الأفراد_الرعاية_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Health_Personal_Care_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 5331449 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Digital_Ebook_Purchase_v1_01
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Digital_Ebook_Purchase_v1_01')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 5101693 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
الصفحة الرئيسية_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Home_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 6221559 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Wireless_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Wireless_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 9002021 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Books_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Books_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 10319090 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Digital_Ebook_Purchase_v1_00
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:amazon_us_reviews/Digital_Ebook_Purchase_v1_00')
- الوصف :
Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.
Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).
Each Dataset contains the following columns:
- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الانقسامات :
انشق، مزق | أمثلة |
---|---|
'train' | 12520722 |
- الميزات :
{
"marketplace": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"customer_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_parent": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_title": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"product_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"star_rating": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"helpful_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"total_votes": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"vine": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"verified_purchase": {
"num_classes": 2,
"names": [
"N",
"Y"
],
"id": null,
"_type": "ClassLabel"
},
"review_headline": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_body": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"review_date": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}