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IRAL
2003
ACM

An approach for combining content-based and collaborative filters

11 years 10 months ago
An approach for combining content-based and collaborative filters
In this work, we apply a clustering technique to integrate the contents of items into the item-based collaborative filtering framework. The group rating information that is obtained from the clustering result provides a way to introduce content information into collaborative recommendation and solves the cold start problem. 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.
Qing Li, Byeong Man Kim
Added 05 Jul 2010
Updated 05 Jul 2010
Type Conference
Year 2003
Where IRAL
Authors Qing Li, Byeong Man Kim
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