This dataset contains a small sample of the Yahoo! Movies community's preferences for various movies, rated on a scale from A+ to F. Users are represented as meaningless anonymous numbers so that no identifying information is revealed. The dataset also contains a large amount of descriptive information about many movies released prior to November 2003, including cast, crew, synopsis, genre, average ratings, awards, etc. The dataset may be used by researchers to validate recommender systems or collaborative filtering algorithms, including hybrid content and collaborative filtering algorithms. The dataset may serve as a testbed for relational learning and data mining algorithms as well as matrix and graph algorithms including PCA and clustering algorithms. The size of this dataset is 23 MB.

Here are all the papers published on this Webscope Dataset:

• Heterogeneous Source Consensus Learning via Decision Propagation and Negotiation
• Locally Adaptive Neighborhood Selection for Collaborative Filtering Recommendations
• Item Weighting Techniques for Collaborative Filtering
• A Framework for Multi-objective Clustering and its Application to Co-location Mining
• Online Selection of Mediated and Domain-Specific Predictions for Improved Recommender Systems
• Neural Semantic Personalized Ranking for item cold-start recommendation

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