MovieLens 1M

doi:doi:10.57702/lih52fgw

MovieLens 1M

The associated task is to predict the movie rating on a 5-star scale. This dataset contains 6,040 users, 3,900 movies, and 1,000,209 ratings, i.e., rating matrix is 4.26% full.

BibTex:

@dataset{Himan_Abdollahpouri_and_Robin_Burke_and_Masoud_Mansoury_and_Bamshad_Mobasher_2024,
    abstract = {The associated task is to predict the movie rating on a 5-star scale. This dataset contains 6,040 users, 3,900 movies, and 1,000,209 ratings, i.e., rating matrix is 4.26% full.},
    author = {Himan Abdollahpouri and Robin Burke and Masoud Mansoury and Bamshad Mobasher},
    doi = {10.57702/lih52fgw},
    institution = {No Organization},
    keyword = {'Collaborative Filtering', 'Collaborative filtering', 'Movie Ratings', 'Movie ratings', 'MovieLens', 'MovieLens 1M', 'Rating', 'Rating Data', 'Rating Dataset', 'Rating Matrix', 'Recommendation Systems', 'Recommender Systems', 'Recommender systems', 'movie ratings', 'movie recommendations', 'recommendation systems', 'user ratings', 'user-item interactions', 'user-item ratings'},
    month = {dec},
    publisher = {TIB},
    title = {MovieLens 1M},
    url = {https://service.tib.eu/ldmservice/dataset/movielens-1m},
    year = {2024}
}