Clustering web transactions using rough approximation

被引：52

作者：

De, SK

Krishna, PR

机构：

[1] IDRBT, Inst Dev & Res Banking Technol, Hyderabad 500057, Andhra Pradesh, India

[2] XLRI Jamshedpur, Jamshedpur 831001, Bihar, India

来源：

FUZZY SETS AND SYSTEMS | 2004年 / 148卷 / 01期

关键词：

web usage mining; rough sets; web access pattern; similarity upper approximation;

D O I：

10.1016/j.fss.2004.03.010

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Web usage mining is the application of data mining techniques to web log data repositories. Discovering user access patterns from web access log is increasing the importance of information to build up adaptive web server according to the individual user's behavior. In general, the discovered knowledge or any unexpected rules are likely to be imprecise or incomplete, which requires a framework with soft computing techniques like rough sets. In this paper, we present a rough approximation-based clustering to cluster web transactions from web access logs. Using this approach, users can effectively mine web log records to discover web page access patterns. (C) 2004 Elsevier B.V. All rights reserved.

引用

页码：131 / 138

页数：8

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