標題: PNP: Mining of profile navigational patterns
作者: Li, HF
Shan, MK
資訊工程學系
Department of Computer Science
關鍵字: Web mining;Web usage mining;categorical;quantitative;navigation sequence;profile navigation patterns;attribute;PNP
公開日期: 2002
摘要: Web usage mining is a key knowledge discovery research and as such has been well researched. So far, this research has focused mainly on databases containing access log data only. However, many real-world databases contain users profile data and current solutions for this situation are still insufficient. In this paper we have a large database containing of user profile information together with users web-pages navigational patterns. The user profile data includes quantitative attributes, such as salary or age, and categorical attributes, such as sex or marital status. We introduce the concept of profile navigation patterns, which discusses the problem of relating user profile information to navigation behavior. An example of such profile navigation pattern might be "20% of married people between age 25 and 30 have the similar navigational behavior <(ac)(c,b)(b,e)(e,a)(od)> ", where a, b, c, d, e are web pages in a web site. The navigation sequences may contain the generic traversal behavior, e.g. trend to backward moves, cycles etc. The objective of mining profile navigation patterns is to identify browser profile for web personalization. We present PNP, a new algorithm that discovers these profile navigation patterns. Scale-up experiments show that PNP scales linearly with the number of transactions.
URI: http://hdl.handle.net/11536/18739
http://dx.doi.org/10.1117/12.460235
ISBN: 0-8194-4480-4
ISSN: 0277-786X
DOI: 10.1117/12.460235
期刊: DATA MINING AND KNOWLEDGE DISCOVERY: THEORY, TOOLS AND TECHNOLOGY IV
Volume: 4730
起始頁: 252
結束頁: 260
顯示於類別:會議論文


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  1. 000176405500030.pdf