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http://dx.doi.org/10.14400/JDC.2014.12.8.329

A New Collaborative Filtering Method for Movie Recommendation Using Genre Interest  

Lee, Soojung (Dept. of Computer Education, Gyeongin National Univ. of Education)
Publication Information
Journal of Digital Convergence / v.12, no.8, 2014 , pp. 329-335 More about this Journal
Abstract
Collaborative filtering has been popular in commercial recommender systems, as it successfully implements social behavior of customers by suggesting items that might fit to the interests of a user. So far, most common method to find proper items for recommendation is by searching for similar users and consulting their ratings. This paper suggests a new similarity measure for movie recommendation that is based on genre interest, instead of differences between ratings made by two users as in previous similarity measures. From extensive experiments, the proposed measure is proved to perform significantly better than classic similarity measures in terms of both prediction and recommendation qualities.
Keywords
Recommender system; Similarity measure; Collaborative filtering; Memory-based collaborative filtering; Content-based filtering;
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