Improved Collaborative Filtering Method Applied in Movie Recommender System

Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 146)

Abstract

Due to the rapid growth of internet, a useful technology named recommender system (RS) become an effective application to make recommendations to users, nowadays, many collaborative recommender systems (CRS) have succeeded in some fields like movies and music web applications; however, there are also some ways for them to be a more effective RS. This paper introduces a new item-based collaborative filtering method which uses mixed similarity, and it also can solve the cold start problem. A series of experiments are accomplished to indicate that the new method can make a better recommendation than the pure item-based collaborative filtering method.

Keywords

recommender systems collaborative filtering item-based cold start problem mixed similarity 

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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Department of AutomationXiamen UniversityXiamenChina

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