It contains trust relationships amongst users and spans more than a decade, from January 2001 to November 2013. This dataset was collected from, a popular online consumer review website. The items from each outfit are viewed as the items being recommended to users, where each item consists of attributes such as category and title. This dataset is a fashion outfit dataset collected from Alibaba online shopping systems in the paper POG. The total number of reviews is 233.1 million and the number of categories is 29 (142.8 million and 24 in 2014) and current data includes reviews in the range May 1996 - Oct 2018. Amazon 2018: This Dataset is an updated version of the Amazon review dataset released in 2014. Amazon 2014: This dataset contains product reviews and metadata from Amazon, including 24 categories and 142.8 million reviews spanning May 1996 - July 2014.Our processed datasets are detailed here. Baidu Wangpan (Password: e272), Google Drive.ĭatasets link and brief introduction ShoppingĪmazon Review Data includes reviews (ratings, text, helpfulness votes) and product metadata (descriptions, category information, price, brand, and image features), which includes a previous version in 2014 and an updated version in 2018. Please refer to conversion tools.ĭirectly download the processed atomic files. We provide two ways to convert these datasets into atomic files:ĭownload the raw dataset and process it with conversion tools we provide in this repository. Which is a kind of data format defined by RecBole. In order to use RecBole, you need to convert these original datasets to the atomic file To test the performance of different recommender models on these datasets easily.įor more information about RecBole, please refer to RecBole. Which is a unified, comprehensive and efficient recommendation library.Īfter converting to the atomic files, you can use RecBole This is a repository of public data sources for Recommender Systems (RS).Īll of these recommendation datasets can convert to the atomic files
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