Hybrid recommendation approaches: Collaborative filtering via valuable content information

Ya Yueh Shih, Duen-Ren Liu

研究成果: Conference article同行評審

30 引文 斯高帕斯(Scopus)

摘要

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.

原文English
頁數1
期刊Proceedings of the Annual Hawaii International Conference on System Sciences
DOIs
出版狀態Published - 10 十一月 2005
事件38th Annual Hawaii International Conference on System Sciences - Big Island, HI, United States
持續時間: 3 一月 20056 一月 2005

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