Clustering Fuzzy Web Transactions with Rough k-Means

被引：1
作者：
Shi, Peilin [1 ]
机构：
[1] Taiyuan Univ Technol, Dept Math, Taiyuan, Shanxi, Peoples R China
来源：
AST: 2009 INTERNATIONAL E-CONFERENCE ON ADVANCED SCIENCE AND TECHNOLOGY, PROCEEDINGS | 2009年
关键词：
clustering; fuzzy variable; rough set; user access patterns;
D O I：
10.1109/AST.2009.23
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Time duration and presence of a web page are two factors disclosing web users' interest. The time duration on a web page is characterized as a fuzzy linguistic variable because it is easily understandable for people and the subtle difference between two durations is disregarded. Thus a web access pattern is transformed as a fuzzy web access pattern, which is a fuzzy vector that are composed of n fuzzy linguistic variable or 0. Furthermore, the clusters in web access patterns do not necessarily have crisp boundaries. This paper proposes a modified k-means clustering algorithm based oil properties of rough set to group the gained fuzzy, web access patterns. Finally, an example is provided for clustering the given web access patterns. The results are proved to be effective.
引用
收藏
页码：48 / 51
页数：4
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