We designed and built a web-based movie recommender system. We used association rule mining to implement two data filtering methods. Content-based filtering identifies sets of common attributes of the movies that the user has liked in the past, while collaborative filtering associates users with each other based on similarities in taste. By combining content- and collaborative-base filtering, we obtained recommendations with a higher precision than either method individually.
Worcester Polytechnic Institute
Major Qualifying Project
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