On-line recommendation method based on graph model and maximizing information retention
LI Yong-li1,2, WU Chong2, WANG Kun-sheng1
1. Institute of No.710, China Aerospace Science and Technology Corporation, Beijing 100037, China;
2. School of Management, Harbin Institute of Technology, Harbin 150001, China
Abstract:The development of E-commence calls for an effective and accurate recommendation method which not only convinces customers, but also accelerates circulation of commodities and promotes economic development. The existed recommendation methods paid attention to either the similarity of goods or that of customers, thus could not trade off the two aspects of information and make full use of them. In view of the above, this paper proposed recommendation method on the basis of graph model, which synthesized the similarity of customers and goods. The method built a comprehensive assessment model able to be transformed into its equivalent evaluation matrix and established an algorithm based on the above evaluation matrix with the aim of maximizing the retention of information. What’s more, this paper compared it with the benchmark methods. As a result, the numerical experiments show that the method has short-time calculations, high accuracy and is proper for real-time online recommendation.
李永立, 吴冲, 王崑声. 基于图论和信息最大化保留的在线推荐方法[J]. 系统工程理论与实践, 2011, 31(9): 1718-1725.
LI Yong-li, WU Chong, WANG Kun-sheng. On-line recommendation method based on graph model and maximizing information retention. Systems Engineering - Theory & Practice, 2011, 31(9): 1718-1725.
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