According to the needs of personalized recommendation service and the problem of high-dimension and sparse user-document visited data, an inter-user comparation based dimension reduction method and K-hirachical clustering arithmetic is utilized to analyze the user clustering procedure based on users’ resources evaluation data colloction. On the basis of those, an experimental system of user clustering is also designed and developed by applying Java open source technology.
颜端武,罗胜阳,成晓 . 协同推荐中基于用户-文档矩阵的用户聚类研究*[J]. 现代图书情报技术, 2007, 2(3): 25-28.
Yan Duanwu,Luo Shengyang,Cheng Xiao . Toward User-Document Matrix Based User Clustering for Collaborative Recommendation. New Technology of Library and Information Service, 2007, 2(3): 25-28.
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