Intelligent Techniques for Web Personalization IJCAI 2003 Workshop,
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Subseries of Lecture Notes in Computer Science
3169
Bamshad Mobasher Sarabjot SinghAnand (Eds.)
Intelligent Techniques for Web Personalization IJCAI 2003 Workshop, ITWP 2003 Acapulco, Mexico, August 11, 2003 Revised Selected Papers
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Series Editors Jaime G. Carbonell, Carnegie Mellon University, Pittsburgh, PA, USA Jörg Siekmann, University of Saarland, Saarbrücken, Germany Volume Editors Bamshad Mobasher DePaul University, Center for Web Intelligence School of Computer Science, Telecommunication and Information Systems Chicago, Illinois, USA E-mail: [email protected] Sarabjot Singh Anand University of Warwick, Department of Computer Science Coventry CV4 7AL, UK E-mail: [email protected]
Library of Congress Control Number: 2005935451
CR Subject Classification (1998): I.2.11, K.4.1, K.4.4, C.2, H.3.4-5, H.5.3, I.2 ISSN ISBN-10 ISBN-13
0302-9743 3-540-29846-0 Springer Berlin Heidelberg New York 978-3-540-29846-5 Springer Berlin Heidelberg New York
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Preface
Web personalization can be defined as any set of actions that can tailor the Web experience to a particular user or set of users. The experience can be something as casual as browsing a Web site or as (economically) significant as trading stock or purchasing a car. The actions can range from simply making the presentation more pleasing to anticipating the needs of a user and providing customized and relevant information. To achieve effective personalization, organizations must rely on all available data, including the usage and click-stream data (reflecting user behavior), the site content, the site structure, domain knowledge, user demographics and profiles. In addition, efficient and intelligent techniques are needed to mine these data for actionable knowledge, and to effectively use the discovered knowledge to enhance the users’ Web experience. These techniques must address important challenges emanating from the size and the heterogeneity of the data, and the dynamic nature of user interactions with the Web. E-commerce and Web information systems are rich sources of difficult problems and challenges for AI researchers. These challenges include the scalability of the personalization solut
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