Hybrid Recommendation Approaches: Collaborative Filtering via Valuable Content Information

Authors:
Ya-Yueh Shih;Duen-Ren Liu
Affiliations:
MingHsin University of Science & Technology/ National Chiao Tung University;National Chiao Tung University
Venue:
HICSS '05 Proceedings of the Proceedings of the 38th Annual Hawaii International Conference on System Sciences - Volume 08
Year:
2005

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Abstract

Collaborative filtering (CF) method has been successfully used in recommender systems to support product recommendation, but it has several limitations. This work uses customer demands derived from the frequent purchased products in each industry as valuable content information. Accordingly, this work explores two hybrid approaches each of which combines CF and customer demands to improve quality of recommendation. Valuable content information is also included as a factor in making recommendations for re-ranking candidate products. The experimental results indicate that the quality of recommendation obtained by the combined methods is promising.