WEBKDD 2002 - Mining Web Data for Discovering Usage Patterns and Profiles
1 WorkshopTheme Data mining as a discipline aims to relate the analysis of large amounts of user data to shed light on key business questions. Web usage mining in particular, a relatively young discipline, investigates methodologies and techniques that -
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Subseries of Lecture Notes in Computer Science
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Osmar R. Za¨ıane Jaideep Srivastava Myra Spiliopoulou Brij Masand (Eds.)
WEBKDD 2002 – Mining Web Data for Discovering Usage Patterns and Profiles 4th International Workshop Edmonton, Canada, July 23, 2002 Revised Papers
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Series Editors Jaime G. Carbonell, Carnegie Mellon University, Pittsburgh, PA, USA J¨org Siekmann, University of Saarland, Saarbr¨ucken, Germany Volume Editors Osmar R. Za¨ıane University of Alberta, Department of Computing Science Edmonton, Alberta, T6G 2E8 Canada E-mail: [email protected] Jaideep Srivastava University of Minnesota, Computer Science and Engineering Minneapolis, MN 55455, USA E-mail: [email protected] Myra Spiliopoulou Otto-von-Guericke University of Magdeburg, Faculty of Computer Science Institute of Technical and Business Information Systems P.O. Box 4120, 39016 Magdeburg, Germany E-mail: [email protected] Brij Masand Data Miners Inc. 77 North Washington Street, 9th Floor, Boston, MA 02114, USA E-mail: [email protected] Cataloging-in-Publication Data applied for A catalog record for this book is available from the Library of Congress. Bibliographic information published by Die Deutsche Bibliothek Die Deutsche Bibliothek lists this publication in the Deutsche Nationalbibliografie; detailed bibliographic data is available in the Internet at . CR Subject Classification (1998): I.2, H.2.8, H.3-4, K.4, C.2 ISSN 0302-9743 ISBN 3-540-20304-4 Springer-Verlag Berlin Heidelberg New York This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, re-use of illustrations, recitation, broadcasting, reproduction on microfilms or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer-Verlag. Violations are liable for prosecution under the German Copyright Law. Springer-Verlag Berlin Heidelberg NewYork a member of BertelsmannSpringer Science+Business Media GmbH www.springeronline.com c Springer-Verlag Berlin Heidelberg 2003 Printed in Germany Typesetting: Camera-ready by author, data conversion by PTP-Berlin GmbH Printed on acid-free paper SPIN: 10928684 06/3142 543210
Preface
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Workshop Theme
Data mining as a discipline aims to relate the analysis of large amounts of user data to shed light on key business questions. Web usage mining in particular, a relatively young discipline, investigates methodologies and techniques that address the unique challenges of discovering insights from Web usage data, aiming to evaluate Web usability, understand the interests and expectations of users and assess the effectiveness of content delivery. The maturing and expanding Web presents a key driving force in the rapid growth of electronic commerce
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