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2003 IEEE/WIC International Conference on Web Intelligence (WI'03)   p. 33
Clustering Approach for Hybrid Recommender System
Qing Li, Kumoh National Institute of Technology
Byeong Man Kim, Kumoh National Institute of Technology

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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/WI.2003.1241167
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Abstract
Recommender system is a kind of web intelligence techniques to make a daily information filtering for people. In this work1, Clustering techniques have been applied to the item-based collaborative filtering framework to solve the cold start problem. It also suggests a way to integrate the content information into the collaborative filtering. Extensive experiments have been conducted on MovieLens data to analyze the characteristics of our technique. The results show that our approach contributes to the improvement of prediction quality of the item-based collaborative filtering, especially for the cold start problem.
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Citation:  Qing Li, Byeong Man Kim, "Clustering Approach for Hybrid Recommender System," wi, p. 33,  2003 IEEE/WIC International Conference on Web Intelligence (WI'03),  2003