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Erschienen in:
2018 | OriginalPaper | Buchkapitel
Movie Recommendation System: Hybrid Information Filtering System
verfasst von : Kartik Narendra Jain, Vikrant Kumar, Praveen Kumar, Tanupriya Choudhury
Erschienen in: Intelligent Computing and Information and Communication
Verlag: Springer Singapore
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Abstract
The movie recommendation system is a hybrid filtering system that performs both collaborative and content-based filtering of data to provide recommendations to users regarding movies. The system conforms to a different approach where it seeks the similarity of users among others clustered around the various genres and utilizes his preference of movies based on their content in terms of genres as the deciding factor of the recommendation of the movies to them. The system is based on the belief that a user rates movies in a similar fashion to other users that harbor the same state as the current user and is also affected by the other activities (in terms of rating) he performs with other movies. It follows the hypothesis that a user can be accurately recommended media on the basis others interests (collaborative filtering) and the movies themselves (content-based filtering).