A Fast Collaborative Filtering Algorithm for Implicit Binary Data

摘要：

Item-based and user-based collaborative filtering are two well-known algorithms for recommender system in E commerce. Both the algorithms make use of similarity matrix whose elements represent the similarity of each item pairs or user pairs. A fast algorithm for item-based similarity matrix computation using cosine similarity metric was reviewed and applied for user-based one with some modification. Th results show that the fast algorithm can blend well with other similarity metrics, and it can greatly improve the computational performance.

关键词： Recommender system Collaborative filtering Similarity matrix Binary data

作者: Manzhao Bu Shijian Luo Ji He

作者单位: College of Computer ,Sctence and TecHnology Zhejiang University Hangzhou, Zhejiang Province 310027, China

会议类型: 国际会议

会议名称: 2009 IEEE 10th International Conference on Computer-Aided Industrial Design & Conceptual Design(2009 IEEE 第十届国际计算机辅助工业设计与概念设计学术会议 CAID&CD2009)

会议地点: 温州

会议语种:英文

页码: 973-976

在线出版日期: 2009-11-26（万方平台首次上网日期，不代表论文的发表时间）