9 datasets found

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

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

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.

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...

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...

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...

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

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,...

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...