Advances in Web Mining and Web Usage Analysis

7th International Workshop on Knowledge Discovery on the Web, WebKDD 2005, Chicago, IL, USA, August 21, 2005. Revised Papers

  • Olfa Nasraoui
  • Osmar Zaïane
  • Myra Spiliopoulou
  • Bamshad Mobasher
  • Brij Masand
  • Philip S. Yu
Conference proceedings WebKDD 2005

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4198)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 4198)

Table of contents

  1. Front Matter
  2. Lin Lu, Margaret Dunham, Yu Meng
    Pages 1-17
  3. Vincent Schickel-Zuber, Boi Faltings
    Pages 39-57
  4. Miha Grčar, Dunja Mladenič, Blaž Fortuna, Marko Grobelnik
    Pages 58-76
  5. Colin DeLong, Prasanna Desikan, Jaideep Srivastava
    Pages 77-95
  6. Bamshad Mobasher, Robin Burke, Chad Williams, Runa Bhaumik
    Pages 96-118
  7. Bhushan Shankar Suryavanshi, Nematollaah Shiri, Sudhir P. Mudur
    Pages 119-138
  8. Charu C. Aggarwal, Philip S. Yu
    Pages 139-157
  9. Back Matter

About these proceedings

Introduction

Thisbookcontainsthepostworkshopproceedingsofthe7thInternationalWo- shop on Knowledge Discovery from the Web, WEBKDD 2005. The WEBKDD workshop series takes place as part of the ACM SIGKDD International Conf- ence on Knowledge Discovery and Data Mining (KDD) since 1999. The discipline of data mining delivers methodologies and tools for the an- ysis of large data volumes and the extraction of comprehensible and non-trivial insights from them. Web mining, a much younger discipline, concentrates on the analysisofdata pertinentto theWeb.Web mining methods areappliedonusage data and Web site content; they strive to improve our understanding of how the Web is used, to enhance usability and to promote mutual satisfaction between e-business venues and their potential customers. In the last years, the interest for the Web as medium for communication, interaction and business has led to new challenges and to intensive, dedicated research. Many of the infancy problems in Web mining have now been solved but the tremendous potential for new and improved uses, as well as misuses, of the Web are leading to new challenges.

Keywords

Web access seq association rule mining data mining filtering graph mining knowledge knowledge discovery ontologies ontology recommender system security semantics taxonimic context usage pattern discovery user profiling

Editors and affiliations

  • Olfa Nasraoui
    • 1
  • Osmar Zaïane
    • 2
  • Myra Spiliopoulou
    • 3
  • Bamshad Mobasher
    • 4
  • Brij Masand
    • 5
  • Philip S. Yu
    • 6
  1. 1.Knowledge Discovery & Web Mining LabUniversity of LouisvilleLouisvilleUSA
  2. 2.University of AlbertaCanada
  3. 3.Faculty of Computer ScienceOtto-von-Guericke-University MagdeburgGermany
  4. 4.Center for Web Intelligence School of ComputingDePaul UniversityChicagoUSA
  5. 5.Data Miners Inc.BostonUSA
  6. 6.University of IllinoisChicagoUSA

Bibliographic information

  • DOI https://doi.org/10.1007/11891321
  • Copyright Information Springer-Verlag Berlin Heidelberg 2006
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-540-46346-7
  • Online ISBN 978-3-540-46348-1
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book