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结合用户交易情况的改进聚类算法
引用本文:何典,宋中山,梁英. 结合用户交易情况的改进聚类算法[J]. 计算机应用与软件, 2007, 24(11): 177-179,191
作者姓名:何典  宋中山  梁英
作者单位:湖南商学院计算机与电子工程系,湖南,长沙,410205;中南民族大学计算机科学学院,湖北,武汉,430074
摘    要:对通过URL-UserID关联矩阵得到页面聚类和用户聚类的算法进行了研究.指出了可以结合用户的交易结果来评价用户对商品页面的兴趣度,并给出了改进后的算法和计算过程,从而关联矩阵元素的权值能够更准确地反映用户对商品页面的感兴趣程度,使聚类分析结果更佳.

关 键 词:Web挖掘  聚类分析  关联矩阵
修稿时间:2005-10-14

AN IMPROVED ALGORITHM FOR CLUSTERING ANALYSIS INTEGRATING WITH THE TRADE DATA
He Dian,Song Zhongshan,Liang Ying. AN IMPROVED ALGORITHM FOR CLUSTERING ANALYSIS INTEGRATING WITH THE TRADE DATA[J]. Computer Applications and Software, 2007, 24(11): 177-179,191
Authors:He Dian  Song Zhongshan  Liang Ying
Affiliation:1. Department of Computer and Electronic Engineering, Hunan Business College, Changsha 410205,Hunan, China; 2 . School of Computer Science, SCUEC, Wuhan 430074, Hubei, China
Abstract:The page clustering and user clustering analysis based on the URL-UserID association matrix are studied.That the trade data of users can be used to estimate the interest of users in the merchandise page is pointed out.The improved algorithm and computation process are detailed.The right of element in the matrix can reflect the degree of users' interest in the merchandise page more accurately,which makes the result of clustering analysis better.
Keywords:Web mining   Clustering analysis   Association matrix
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