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Proceedings Paper

PNP: mining of profile navigational patterns
Author(s): Hua-Fu Li; Man-Kwan Shan
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Paper Abstract

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 user web-pages navigation 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 navigational behavior. An example of such profile navigation pattern might be 20% of married people between age 25 and 30 have the similar navigational behavior <(a,c)(c,h)(h,i)(i,h)(h,l)>, where a, c, h, i, l are web pages in a web site. The navigation patterns 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 give an algorithm for mining such profile navigation patterns. Our method (algorithm PNP) can discover profile navigation patterns efficiently. We also present new inclination measurements to identify the interesting profile navigational patterns. Experimental results show the efficiency and scalability of PNP.

Paper Details

Date Published: 12 March 2002
PDF: 9 pages
Proc. SPIE 4730, Data Mining and Knowledge Discovery: Theory, Tools, and Technology IV, (12 March 2002); doi: 10.1117/12.460235
Show Author Affiliations
Hua-Fu Li, National Chiao Tung Univ. (Taiwan)
Man-Kwan Shan, National Cheng Chi Univ. (Taiwan)

Published in SPIE Proceedings Vol. 4730:
Data Mining and Knowledge Discovery: Theory, Tools, and Technology IV
Belur V. Dasarathy, Editor(s)

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