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IEICE Transactions on Information and Systems 2005 E88-D(5):993-1003; doi:10.1093/ietisy/e88-d.5.993
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Copyright © 2005 The Institute of Electronics, Information and Communication Engineers

Regular Section -- Papers -- Artificial Intelligence and Cognitive Science

Acquisition and Maintenance of Knowledge for Online Navigation Suggestions

Juan D. VELÁSQUEZ1, Richard WEBER2, Hiroshi YASUDA1 and Terumasa AOKI1

1 The authors are with Research Center for Advanced Science and Technology, University of Tokyo, Tokyo, 153–8904 Japan. E-mail: jvelasqu{at}mpeg.rcast.u-tokyo.ac.jp, 2 The author is with Center for Collaborative Research, University of Tokyo, Tokyo, 153–8904 Japan. On leave from Department of Industrial Engineering, University of Chile. E-mail: weber{at}vp.ccr.u-tokyo.ac.jp

The Internet has become an important medium for effective marketing and efficient operations for many institutions. Visitors of a particular web site leave behind valuable information on their preferences, requirements, and demands regarding the offered products and/or services. Understanding these requirements online, i.e., during a particular visit, is both a difficult technical challenge and a tremendous business opportunity. Web sites that can provide effective online navigation suggestions to their visitors can exploit the potential inherent in the data such visits generate every day. However, identifying, collecting, and maintaining the necessary knowledge that navigation suggestions are based on is far from trivial. We propose a methodology for acquiring and maintaining this knowledge efficiently using data mart and web mining technology. Its effectiveness has been shown in an application for a bank's web site.

Key Words: knowledge discovery in data bases, web mining, online suggestions, data mart

Manuscript received November 6, 2003. Manuscript revised May 13, 2004.


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