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amazon_reviews_multi

Referanslar:

tüm_diller

Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:

ds = tfds.load('huggingface:amazon_reviews_multi/all_languages')

Tanım :

We provide an Amazon product reviews dataset for multilingual text classification. The dataset contains reviews in English, Japanese, German, French, Chinese and Spanish, collected between November 1, 2015 and November 1, 2019. Each record in the dataset contains the review text, the review title, the star rating, an anonymized reviewer ID, an anonymized product ID and the coarse-grained product category (e.g. ‘books’, ‘appliances’, etc.) The corpus is balanced across stars, so each star rating constitutes 20% of the reviews in each language.

For each language, there are 200,000, 5,000 and 5,000 reviews in the training, development and test sets respectively. The maximum number of reviews per reviewer is 20 and the maximum number of reviews per product is 20. All reviews are truncated after 2,000 characters, and all reviews are at least 20 characters long.

Note that the language of a review does not necessarily match the language of its marketplace (e.g. reviews from amazon.de are primarily written in German, but could also be written in English, etc.). For this reason, we applied a language detection algorithm based on the work in Bojanowski et al. (2017) to determine the language of the review text and we removed reviews that were not written in the expected language.

Lisans : Çok Dilli Amazon Reviews Corpus'a ("Reviews Corpus") erişerek, Reviews Corpus'un Amazon.com Kullanım Koşullarına tabi bir Amazon Hizmeti olduğunu kabul etmiş olursunuz ( https://www.amazon.com/gp/help/ customer/display.html/ref=footer_cou?ie=UTF8&nodeId=508088 ) ve aşağıdaki ek koşullarla bunlara bağlı kalmayı kabul edersiniz:

Kullanım Koşulları kapsamında verilen lisans haklarına ek olarak Amazon veya içerik sağlayıcıları, akademik araştırma amacıyla Reviews Corpus'a erişmeniz ve onu kullanmanız için size sınırlı, münhasır olmayan, devredilemez, alt lisansı verilemez, iptal edilebilir bir lisans verir. Reviews Corpus'u veya içeriğini yeniden satamaz, yeniden yayınlayamaz veya herhangi bir ticari amaçla kullanamazsınız; buna, Reviews Corpus'un bir finansman veya danışmanlık sözleşmesiyle, stajyerlikle veya sonuçların geçerli olduğu diğer ilişkilerle ilgili araştırmalar gibi ticari araştırmalar için kullanılması da dahildir. bir ücret karşılığında sağlanır veya kar amacı güden bir kuruluşa teslim edilir. (a) Reviews Corpus'taki içeriği herhangi bir kişisel bilgiyle (Amazon müşteri hesapları dahil) bağlayamaz veya ilişkilendiremezsiniz veya (b) Reviews Corpus'taki herhangi bir içeriğin yazarının kimliğini belirlemeye çalışamazsınız. Yukarıdaki koşullardan herhangi birini ihlal etmeniz halinde, Reviews Corpus'a erişme ve onu kullanma lisansınız, Amazon'un sahip olabileceği diğer haklara veya çözüm yollarına halel getirmeksizin otomatik olarak feshedilecektir.

Sürüm : 1.0.0
Bölünmeler :

Bölmek	Örnekler
`'test'`	30000
`'train'`	1200000
`'validation'`	30000

Özellikler :

{
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "reviewer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "stars": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "language": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

de

Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:

ds = tfds.load('huggingface:amazon_reviews_multi/de')

Tanım :

We provide an Amazon product reviews dataset for multilingual text classification. The dataset contains reviews in English, Japanese, German, French, Chinese and Spanish, collected between November 1, 2015 and November 1, 2019. Each record in the dataset contains the review text, the review title, the star rating, an anonymized reviewer ID, an anonymized product ID and the coarse-grained product category (e.g. ‘books’, ‘appliances’, etc.) The corpus is balanced across stars, so each star rating constitutes 20% of the reviews in each language.

For each language, there are 200,000, 5,000 and 5,000 reviews in the training, development and test sets respectively. The maximum number of reviews per reviewer is 20 and the maximum number of reviews per product is 20. All reviews are truncated after 2,000 characters, and all reviews are at least 20 characters long.

Note that the language of a review does not necessarily match the language of its marketplace (e.g. reviews from amazon.de are primarily written in German, but could also be written in English, etc.). For this reason, we applied a language detection algorithm based on the work in Bojanowski et al. (2017) to determine the language of the review text and we removed reviews that were not written in the expected language.

Lisans : Çok Dilli Amazon Reviews Corpus'a ("Reviews Corpus") erişerek, Reviews Corpus'un Amazon.com Kullanım Koşullarına tabi bir Amazon Hizmeti olduğunu kabul etmiş olursunuz ( https://www.amazon.com/gp/help/ customer/display.html/ref=footer_cou?ie=UTF8&nodeId=508088 ) ve aşağıdaki ek koşullarla bunlara bağlı kalmayı kabul edersiniz:

Sürüm : 1.0.0
Bölünmeler :

Bölmek	Örnekler
`'test'`	5000
`'train'`	200000
`'validation'`	5000

Özellikler :

{
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "reviewer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "stars": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "language": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

tr

Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:

ds = tfds.load('huggingface:amazon_reviews_multi/en')

Tanım :

We provide an Amazon product reviews dataset for multilingual text classification. The dataset contains reviews in English, Japanese, German, French, Chinese and Spanish, collected between November 1, 2015 and November 1, 2019. Each record in the dataset contains the review text, the review title, the star rating, an anonymized reviewer ID, an anonymized product ID and the coarse-grained product category (e.g. ‘books’, ‘appliances’, etc.) The corpus is balanced across stars, so each star rating constitutes 20% of the reviews in each language.

For each language, there are 200,000, 5,000 and 5,000 reviews in the training, development and test sets respectively. The maximum number of reviews per reviewer is 20 and the maximum number of reviews per product is 20. All reviews are truncated after 2,000 characters, and all reviews are at least 20 characters long.

Note that the language of a review does not necessarily match the language of its marketplace (e.g. reviews from amazon.de are primarily written in German, but could also be written in English, etc.). For this reason, we applied a language detection algorithm based on the work in Bojanowski et al. (2017) to determine the language of the review text and we removed reviews that were not written in the expected language.

Lisans : Çok Dilli Amazon Reviews Corpus'a ("Reviews Corpus") erişerek, Reviews Corpus'un Amazon.com Kullanım Koşullarına tabi bir Amazon Hizmeti olduğunu kabul etmiş olursunuz ( https://www.amazon.com/gp/help/ customer/display.html/ref=footer_cou?ie=UTF8&nodeId=508088 ) ve aşağıdaki ek koşullarla bunlara bağlı kalmayı kabul edersiniz:

Sürüm : 1.0.0
Bölünmeler :

Bölmek	Örnekler
`'test'`	5000
`'train'`	200000
`'validation'`	5000

Özellikler :

{
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "reviewer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "stars": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "language": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

es

Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:

ds = tfds.load('huggingface:amazon_reviews_multi/es')

Tanım :

We provide an Amazon product reviews dataset for multilingual text classification. The dataset contains reviews in English, Japanese, German, French, Chinese and Spanish, collected between November 1, 2015 and November 1, 2019. Each record in the dataset contains the review text, the review title, the star rating, an anonymized reviewer ID, an anonymized product ID and the coarse-grained product category (e.g. ‘books’, ‘appliances’, etc.) The corpus is balanced across stars, so each star rating constitutes 20% of the reviews in each language.

For each language, there are 200,000, 5,000 and 5,000 reviews in the training, development and test sets respectively. The maximum number of reviews per reviewer is 20 and the maximum number of reviews per product is 20. All reviews are truncated after 2,000 characters, and all reviews are at least 20 characters long.

Note that the language of a review does not necessarily match the language of its marketplace (e.g. reviews from amazon.de are primarily written in German, but could also be written in English, etc.). For this reason, we applied a language detection algorithm based on the work in Bojanowski et al. (2017) to determine the language of the review text and we removed reviews that were not written in the expected language.

Lisans : Çok Dilli Amazon Reviews Corpus'a ("Reviews Corpus") erişerek, Reviews Corpus'un Amazon.com Kullanım Koşullarına tabi bir Amazon Hizmeti olduğunu kabul etmiş olursunuz ( https://www.amazon.com/gp/help/ customer/display.html/ref=footer_cou?ie=UTF8&nodeId=508088 ) ve aşağıdaki ek koşullarla bunlara bağlı kalmayı kabul edersiniz:

Sürüm : 1.0.0
Bölünmeler :

Bölmek	Örnekler
`'test'`	5000
`'train'`	200000
`'validation'`	5000

Özellikler :

{
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "reviewer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "stars": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "language": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Fr

Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:

ds = tfds.load('huggingface:amazon_reviews_multi/fr')

Tanım :

We provide an Amazon product reviews dataset for multilingual text classification. The dataset contains reviews in English, Japanese, German, French, Chinese and Spanish, collected between November 1, 2015 and November 1, 2019. Each record in the dataset contains the review text, the review title, the star rating, an anonymized reviewer ID, an anonymized product ID and the coarse-grained product category (e.g. ‘books’, ‘appliances’, etc.) The corpus is balanced across stars, so each star rating constitutes 20% of the reviews in each language.

For each language, there are 200,000, 5,000 and 5,000 reviews in the training, development and test sets respectively. The maximum number of reviews per reviewer is 20 and the maximum number of reviews per product is 20. All reviews are truncated after 2,000 characters, and all reviews are at least 20 characters long.

Note that the language of a review does not necessarily match the language of its marketplace (e.g. reviews from amazon.de are primarily written in German, but could also be written in English, etc.). For this reason, we applied a language detection algorithm based on the work in Bojanowski et al. (2017) to determine the language of the review text and we removed reviews that were not written in the expected language.

Lisans : Çok Dilli Amazon Reviews Corpus'a ("Reviews Corpus") erişerek, Reviews Corpus'un Amazon.com Kullanım Koşullarına tabi bir Amazon Hizmeti olduğunu kabul etmiş olursunuz ( https://www.amazon.com/gp/help/ customer/display.html/ref=footer_cou?ie=UTF8&nodeId=508088 ) ve aşağıdaki ek koşullarla bunlara bağlı kalmayı kabul edersiniz:

Sürüm : 1.0.0
Bölünmeler :

Bölmek	Örnekler
`'test'`	5000
`'train'`	200000
`'validation'`	5000

Özellikler :

{
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "reviewer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "stars": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "language": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

evet

Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:

ds = tfds.load('huggingface:amazon_reviews_multi/ja')

Tanım :

We provide an Amazon product reviews dataset for multilingual text classification. The dataset contains reviews in English, Japanese, German, French, Chinese and Spanish, collected between November 1, 2015 and November 1, 2019. Each record in the dataset contains the review text, the review title, the star rating, an anonymized reviewer ID, an anonymized product ID and the coarse-grained product category (e.g. ‘books’, ‘appliances’, etc.) The corpus is balanced across stars, so each star rating constitutes 20% of the reviews in each language.

For each language, there are 200,000, 5,000 and 5,000 reviews in the training, development and test sets respectively. The maximum number of reviews per reviewer is 20 and the maximum number of reviews per product is 20. All reviews are truncated after 2,000 characters, and all reviews are at least 20 characters long.

Note that the language of a review does not necessarily match the language of its marketplace (e.g. reviews from amazon.de are primarily written in German, but could also be written in English, etc.). For this reason, we applied a language detection algorithm based on the work in Bojanowski et al. (2017) to determine the language of the review text and we removed reviews that were not written in the expected language.

Lisans : Çok Dilli Amazon Reviews Corpus'a ("Reviews Corpus") erişerek, Reviews Corpus'un Amazon.com Kullanım Koşullarına tabi bir Amazon Hizmeti olduğunu kabul etmiş olursunuz ( https://www.amazon.com/gp/help/ customer/display.html/ref=footer_cou?ie=UTF8&nodeId=508088 ) ve aşağıdaki ek koşullarla bunlara bağlı kalmayı kabul edersiniz:

Sürüm : 1.0.0
Bölünmeler :

Bölmek	Örnekler
`'test'`	5000
`'train'`	200000
`'validation'`	5000

Özellikler :

{
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "reviewer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "stars": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "language": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

zh

Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:

ds = tfds.load('huggingface:amazon_reviews_multi/zh')

Tanım :

We provide an Amazon product reviews dataset for multilingual text classification. The dataset contains reviews in English, Japanese, German, French, Chinese and Spanish, collected between November 1, 2015 and November 1, 2019. Each record in the dataset contains the review text, the review title, the star rating, an anonymized reviewer ID, an anonymized product ID and the coarse-grained product category (e.g. ‘books’, ‘appliances’, etc.) The corpus is balanced across stars, so each star rating constitutes 20% of the reviews in each language.

For each language, there are 200,000, 5,000 and 5,000 reviews in the training, development and test sets respectively. The maximum number of reviews per reviewer is 20 and the maximum number of reviews per product is 20. All reviews are truncated after 2,000 characters, and all reviews are at least 20 characters long.

Note that the language of a review does not necessarily match the language of its marketplace (e.g. reviews from amazon.de are primarily written in German, but could also be written in English, etc.). For this reason, we applied a language detection algorithm based on the work in Bojanowski et al. (2017) to determine the language of the review text and we removed reviews that were not written in the expected language.

Lisans : Çok Dilli Amazon Reviews Corpus'a ("Reviews Corpus") erişerek, Reviews Corpus'un Amazon.com Kullanım Koşullarına tabi bir Amazon Hizmeti olduğunu kabul etmiş olursunuz ( https://www.amazon.com/gp/help/ customer/display.html/ref=footer_cou?ie=UTF8&nodeId=508088 ) ve aşağıdaki ek koşullarla bunlara bağlı kalmayı kabul edersiniz:

Sürüm : 1.0.0
Bölünmeler :

Bölmek	Örnekler
`'test'`	5000
`'train'`	200000
`'validation'`	5000

Özellikler :

{
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "reviewer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "stars": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "language": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}