文章基本信息

标题：Personal Recommendation Using a Novel Collaborative Filtering Algorithm in Customer Relationship Management
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作者：Chonghuan Xu
期刊名称：Discrete Dynamics in Nature and Society
印刷版ISSN：1026-0226
电子版ISSN：1607-887X
出版年度：2013
卷号：2013
DOI：10.1155/2013/739460
出版社：Hindawi Publishing Corporation
摘要：With the rapid development of customer relationship management, more and more user recommendation technologies are used to enhance the customer satisfaction. Although there are many good recommendation algorithms, it is still a challenge to increase the accuracy and diversity of these algorithms to fulfill users’ preferences. In this paper, we construct a user recommendation model containing a new method to compute the similarities among users on bipartite networks. Different from other standard similarities, we consider the influence of each object node including popular degree, preference degree, and trust relationship. Substituting these new definitions of similarity for the standard cosine similarity, we propose a modified collaborative filtering algorithm based on multifactors (CF-M). Detailed experimental analysis on two benchmark datasets shows that the CF-M is of high accuracy and also generates more diversity.