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MovieLens is a non-commercial service for personalized movie recommendations. Users rate movies to build a taste profile, and the service recommends other movies. It also offers data, images, trailers, community tags and search tools, and is run by GroupLens at the University of Minnesota.
MovieLens 1M is a stable benchmark dataset of movie ratings containing 1 million ratings from 6000 users on 4000 movies, released in February 2003. It is available as a downloadable archive with a checksum and README.
Agent4Rec is a recommender system simulator with 1,000 LLM-empowered generative agents initialized from the MovieLens-1M dataset. Each agent interacts with personalized movie recommendations page by page and performs actions such as watching, rating, evaluating, exiting and interviewing. It accompanies the paper "On Generative Agents in Recommendation."
Grouplens Datasets is a collection of research datasets compiled by GroupLens Research and made publicly available. The collection includes datasets such as MovieLens, WikiLens, Book-Crossing, Book Genome Dataset, Jester and EachMovie, along with additional research datasets. Users are advised to review associated README files for usage licenses and other relevant details prior to use.
