124 datasets found

Groups: Recommendation Systems Organizations: No Organization

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  • Digital

    The dataset is used for sequential recommendation tasks, and it contains user-item interaction history.

  • Amazon-Luxury

    The dataset is used for sequential recommendation tasks, and it contains user-item interaction history.

  • Amazon Custom Review Dataset

    The dataset is used for sequential recommendation tasks, and it contains user-item interaction history.

  • MovieLens and Amazon Digital Music

    Two popular and publicly accessible datasets: MovieLens (ML) and Amazon Digital Music (AZ).

  • Taobao User Behavior

    The Taobao User Behavior dataset is a subset of user behaviors on Taobao collected within 9 days and consists of more than 70 million samples and 1 million users.

  • Yahoo!Movies dataset

    The dataset used in this paper is Yahoo!Movies dataset provided by Yahoo!Research Alliance Webscope program.

  • FourSquare shopping places dataset

    FourSquare shopping places dataset from 5 cities in Indonesia. It consists of 1) 176 shopping places data, 2) 3844 visitors' reviews, and 3) 14309 users data.

  • Job Application History and Active Job Posting Records

    A dataset of user job application history and active job posting records.

  • MovieLen1M

    The dataset is a two-mode tensor of user and movie ratings, of size 6, 040 × 3, 706.

  • ACC

    The dataset is a continuous tensor representing the three-way interactions (user, action, file), of size 3, 000 × 150 × 30, 000.

  • Beauty

    The Beauty dataset is a product review dataset crawled from Amazon. The data is split into separate datasets by the top-level product category.

  • Instruments

    The dataset used in the paper for continuous-time sequential recommendation task

  • Software

    The dataset is used for sequential recommendation tasks, and it contains user-item interaction history.

  • MQ2008

    The MQ2008 dataset is a large-scale web search dataset, containing approximately 100,000 query-url pairs with relevance scores.

  • MSLR-WEB10K

    The MSLR-WEB10K dataset is a large-scale web search dataset, containing approximately 235,000 query-url pairs with relevance scores.

  • MovieLens100K

    The dataset is used for sequential recommendation tasks, and it contains user-item interaction history.

  • MovieLens-IMDB

    The MovieLens-IMDB dataset is a collection of user ratings for movies, with each rating indicating the user's preference for the movie.

  • Netflix Dataset

    The dataset used in the paper is a Netflix dataset, which is a large-scale matrix factorization problem.

  • Bing-News

    Bing-News is a dataset containing 1,025,192 pieces of implicit feedback collected from the server logs of Bing News.

  • Walmart.com dataset

    The Walmart.com dataset consists of ~100,000 shopping cart snapshots with the customers' continual shopping records.