12 datasets found

Formats: JSON Tags: MovieLens

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  • MovieLens 1M dataset

    The dataset used in this paper is the MovieLens 1M dataset, which contains a 1M 1-5 star ratings by 6,040 users for 3,952 movies.

  • MovieLens100K

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

  • ML1M

    Offline evaluations of recommender systems attempt to estimate users’ satisfaction with recommendations using static data from prior user interactions.

  • 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.

  • MovieLens Latest, MovieLens 1m, MovieLens 10m, Yelp

    The dataset used in the paper is MovieLens Latest, MovieLens 1m, MovieLens 10m, and Yelp.

  • MovieLens 20M Dataset

    The dataset used in this paper is a high-rating movie recommendation system. The objective of the system is to recommend high-rating movies to users, but the ratings for the...

  • MovieLens Boxoffice

    The MovieLens Boxoffice dataset is a large-scale movie recommendation dataset. It contains 99326 user-item interaction records, with each record representing a user's rating of...

  • MovieLens 20m Light

    The MovieLens 20m Light dataset is a large-scale movie recommendation dataset. It contains 20 million user-item interaction records, with each record representing a user's...

  • MovieLens dataset

    The MovieLens dataset contains questions answerable using Wikidata as the knowledge graph, focusing on questions with a single entity and relation.

  • MovieLens

    The dataset is a movie review dataset with five types of nodes (movie, director, tag, writer, and user) and four types of edges (movie-director relation, movie-tag relation,...

  • ML-20M

    A recommender system generates personalized recommendations for a user by computing the preference score of items, sorting the items according to the score, and filtering top-K...

  • MovieLens 20M

    The dataset used in this paper is the MovieLens 20M dataset, which contains ratings from 92,032 users on 20,000 movies.
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