Amazon

doi:doi:10.57702/041adxuj

Amazon

The dataset used in the paper is a series of datasets introduced in [46], comprising large corpora of product reviews crawled from Amazon.com. Top-level product categories on Amazon are treated as separate datasets. We consider two categories, ‘Beauty,’ and ‘Games.’ This dataset is notable for its high sparsity and variability.

BibTex:

@dataset{Amazon_2024,
    abstract = {The dataset used in the paper is a series of datasets introduced in [46], comprising large corpora of product reviews crawled from Amazon.com. Top-level product categories on Amazon are treated as separate datasets. We consider two categories, ‘Beauty,’ and ‘Games.’ This dataset is notable for its high sparsity and variability.},
    author = {Amazon},
    doi = {10.57702/041adxuj},
    institution = {No Organization},
    keyword = {'Amazon', 'Product Reviews', 'Rating Prediction', 'Recommendation Systems', 'Recommender Systems', 'book rating', 'citation networks', 'clothing', 'implicit feedback', 'jewelry', 'matrix factorization', 'network analysis', 'product metadata', 'product reviews', 'recommendation systems', 'recommender systems', 'sentiment analysis', 'shoes', 'text classification', 'topic classification', 'user-item bipartite graph', 'user-item interactions'},
    month = {nov},
    publisher = {TIB},
    title = {Amazon},
    url = {https://service.tib.eu/ldmservice/dataset/amazon},
    year = {2024}
}