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Mining web navigations for intelligence
DOI:10.1016/j.dss.2004.06.011.png)
摘要
En 中文
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.
Keyword:
principal clusters analysis
intelligence
mining
trend analysis
navigation analysis
information overload
web community
期刊
IF:
6.8
论文数:
3.8K
被引数:
1.5W
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引用论文
A solution to Plato's problem: The latent semantic analysis theory of acquisition, induction, and representation of knowledge
PSYCHOLOGICAL REVIEW
IF5.8
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