A Similarity Measuring Method for Product Recommender System
Most online e-stores recommender systems present recommended products in lists to customer. In this way, much information about the mutual similarity between recommended products is lost. This paper suggests to represent the mutual similarities of the recommended products in a two dimensional space, where similar products are located close to each other and dissimilar products far apart. An adaptation of Gowers similarity coefficient based on the attributes of a product is employed to measure dissimilarity.
similarity recommender system multidimensional scaling electronic commerce
Weixin Yao
School of Management Donghua University, Shanghai 200051, P. R. China
国际会议
北京
英文
302-305
2007-08-18（万方平台首次上网日期，不代表论文的发表时间）