Rates of mental illness continue to rise every year. Yet there are nowhere near enough trained mental health professionals available to meet the need. How can technology create new ways to expand m…
Ken Goldberg from UC Berkeley has also released a dataset from the Jester Joke Recommender System. This dataset contains 4.1 million continuous ratings (-10.00 to +10.00) of 100 jokes from 73,496 u…
The 2nd International Workshop on Information Heterogeneity and Fusion in Recommender Systems (HetRec 2011, has released datasets from Delicious, Last.fm Web 2.0, MovieLens, IMDb, and Rotten Tomat…
GroupLens is a research lab in the Department of Computer Science and Engineering at the University of Minnesota, Twin Cities specializing in recommender systems, online communities, mobile and ubi…
Dataset for “User personality and user satisfaction with recommender systems”: Nguyen, T.T., Maxwell Harper, F., Terveen, L. et al. Inf Syst Front (2018) 20: 1173. README.txtpersonality…
Dataset for “Less Can Be More: Exploring Population Rating Dispositions with Partitioned Models in Recommender Systems”: Ruixuan Sun, Ruoyan Kong, Qiao Jin, and Joseph A. Konstan. 2023. Less Can Be…
Dataset for “Learning from Sets of Items in Recommender Systems”. Mohit Sharma, F.Maxwell Harper, and George Karypis, 2019. Learning from Sets of Items in Recommender Systems. In Procee…
Prospective Ph.D. students and current students at the University of Minnesota can learn more about opportunities and requirements for joining GroupLens by visiting the GroupLens faculty web pages.…
Wikipedia is the online encyclopedia that anyone can edit. However, you probably didn’t know that “bots” also edit Wikipedia! Read this blog about conflict among bots—from the Universit…
MovieLens 1M movie ratings. Stable benchmark dataset. 1 million ratings from 6000 users on 4000 movies. Released 2/2003. README.txt ml-1m.zip (size: 6 MB, checksum) Permalink:
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