【Recommender System】The most complete recommendation system data set, including recommendation data sets based on social networks

The most complete recommendation system data download links, including social networks

1. Movie Recommendation Dataset (Social Dataset)

  • FilmTrust

       This dataset is a small dataset scraped from the FilmTrust website in June 2011. Contains user rating information on movies and social information among users. The amount of data is small, only 35497 scoring data. 1853 pieces of social data.

 Download link: https://github.com/guoguibing/librec/tree/3.0.0/data/filmtrust

  • Epinions

        The data set is large in scale and contains user rating information on movies and social information among users. There are two versions of this data set, one of which also includes the distrust relationship information between users.

Download link: http://www.trustlet.org/epinions.html

  • CiaoDVD

        This dataset contains users' ratings on the items they have purchased and social connections among users. This dataset is a dataset of the entire dvd category of UK websites scraped from dvd.ciao.co. in December 2013.

Download link: Datasets

  • watercress movie

        This is an anonymous Douban dataset containing 129,490 unique users and 58,541 independent movie entries.

Download link: pub:data:douban [Irwin King @ Web Intelligence & Social Computing Lab]

  • Flixster

        Flixster is a social movie site that allows users to share movie ratings, discover new movies, and meet others with similar movie tastes.

Download link: https://www.heywhale.com/mw/dataset/5db94936080dc300371e5cb0

                   http://socialcomputing.asu.edu/datasets/Flixster

  • MovieLens

The MovieLens dataset contains multiple users' rating data for multiple movies, as well as movie metadata information and user attribute information.

Download link: MovieLens | GroupLens

  • Recommender Systems and Personalization Datasets

Download link: Recommender Systems Datasets

2. Delicious Recommendation Dataset

  • Delicious

        This dataset contains social network, bookmark and tag information among users from the Delicious social bookmarking system.

Download link: HetRec 2011 | GroupLens

3. Other recommended datasets

  • Yelp dataset

        This dataset is a subset of business, review and user data used for personal, educational and academic purposes. Available in JSON and SQL files, use it to teach students about databases, learn NLP, or sample production data as you learn how to make mobile apps. The dataset is large in size and requires manual extraction of relevant information.

Download link: Yelp Dataset

  • AmazonReviewsDataset

        The dataset contains product reviews and metadata from Amazon and includes 142.8 million reviews between May 1996 and July 2014. This dataset includes reviews (ratings, text, help votes), product metadata (description, category information, price, brand, and image properties), and links (view/buy charts as well). The dataset is large in size and requires manual extraction of relevant information.

Download link: http://jmcauley.ucsd.edu/data/amazon/ 

  • Book Recommendation Dataset BookCrossing

Download link: http://www2.informatik.uni-freiburg.de/~cziegler/BX/ 

  • Clown Online Joke Recommendation Dataset Jester

Download link:  Jester Datasets

  • Bibsonomy

Tag recommendation in social bookmarking system

Download link: BibSonomy Dataset :: dumps for research purposes

  • Taobao Shopping Dataset (Tianchi)

  Download link:  https://tianchi.aliyun.com/dataset/dataDetail?dataId=1

  • Other dataset download links:

1. Large list of recommended system data sets - Programmer Sought https://www.pianshen.com/article/18991225347/

2. Summary of deep learning technology in social recommendation scenarios (dataset attached) _m0_37586850's blog - CSDN blog preface I don't know if you feel it. When the word recommendation is used in daily life, it is often used in social scenarios. Travel to a place and ask friends to recommend tourist attractions, and ask friends to recommend some books to read when learning a certain technology. In terms of many recommendation systems... https://blog.csdn.net/m0_37586850/article/details/109281724

3. Recommended Field Dataset - huangshanshan - Blog Park http://www.grouplens.org/taxonomy/term/14Movielens Dataset: Among them, Movielens-100k and movielens-1M have user ratings for movies, movies https://www.cnblogs.com/startover/p/3261476.html

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Origin blog.csdn.net/weixin_56516468/article/details/123538631