Mining web navigations for intelligence

被引：22

作者：

Wu, H ^{[1
]}

Gordon, M

DeMaagd, K

Fan, WG

机构：

[1] Old Dominion Univ, Norfolk, VA 23529 USA

[2] Univ Michigan, Business Sch, Ann Arbor, MI 48103 USA

[3] Virginia Tech, Blacksburg, VA 24061 USA

来源：

DECISION SUPPORT SYSTEMS | 2006年 / 41卷 / 03期

关键词：

principal clusters analysis; intelligence; mining; trend analysis; navigation analysis; information overload; web community;

D O I：

10.1016/j.dss.2004.06.011

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The Internet is one of the fastest growing areas of intelligence gathering. We present a statistical approach, called principal clusters analysis, for analyzing millions of user navigations on the Web. This technique identifies prominent navigation clusters on different topics. Furthermore, it can determine information items that are useful starting points to explore a topic, as well as key documents to explore the topic in greater detail. Trends can be detected by observing navigation prominence over time. We apply this technique on a large popular website. The results show promise in web intelligence mining. (c) 2004 Elsevier B.V. All rights reserved.

引用

页码：574 / 591

页数：18

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