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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

  • Conference proceedings
  • © 2006

Overview

Editors:
  1. Olfa Nasraoui

    1. Knowledge Discovery & Web Mining Lab, University of Louisville, Louisville, USA

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  2. Osmar Zaïane

    1. University of Alberta, Canada

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  3. Myra Spiliopoulou

    1. Faculty of Computer Science, Otto-von-Guericke-University Magdeburg, Germany

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  4. Bamshad Mobasher

    1. Center for Web Intelligence School of Computing, DePaul University, Chicago, USA

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  5. Brij Masand

    1. Data Miners Inc., Boston, USA

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  6. Philip S. Yu

    1. University of Illinois, Chicago, USA

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

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: WebKDD 2005.

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Table of contents (9 papers)

  1. Front Matter

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  2. Mining Significant Usage Patterns from Clickstream Data

    • Lin Lu, Margaret Dunham, Yu Meng
    Pages 1-17

  3. Using and Learning Semantics in Frequent Subgraph Mining

    • Bettina Berendt
    Pages 18-38

  4. Overcoming Incomplete User Models in Recommendation Systems Via an Ontology

    • Vincent Schickel-Zuber, Boi Faltings
    Pages 39-57

  5. Data Sparsity Issues in the Collaborative Filtering Framework

    • Miha Grčar, Dunja Mladenič, Blaž Fortuna, Marko Grobelnik
    Pages 58-76

  6. USER: User-Sensitive Expert Recommendations for Knowledge-Dense Environments

    • Colin DeLong, Prasanna Desikan, Jaideep Srivastava
    Pages 77-95

  7. Analysis and Detection of Segment-Focused Attacks Against Collaborative Recommendation

    • Bamshad Mobasher, Robin Burke, Chad Williams, Runa Bhaumik
    Pages 96-118

  8. Adaptive Web Usage Profiling

    • Bhushan Shankar Suryavanshi, Nematollaah Shiri, Sudhir P. Mudur
    Pages 119-138

  9. On Clustering Techniques for Change Diagnosis in Data Streams

    • Charu C. Aggarwal, Philip S. Yu
    Pages 139-157

  10. Personalized Search Results with User Interest Hierarchies Learnt from Bookmarks

    • Hyoung-rae Kim, Philip K. Chan
    Pages 158-176

  11. Back Matter

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Other volumes

  1. Advances in Web Mining and Web Usage Analysis

Keywords

About this book

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.

Editors and Affiliations

  • Knowledge Discovery & Web Mining Lab, University of Louisville, Louisville, USA

    Olfa Nasraoui

  • University of Alberta, Canada

    Osmar Zaïane

  • Faculty of Computer Science, Otto-von-Guericke-University Magdeburg, Germany

    Myra Spiliopoulou

  • Center for Web Intelligence School of Computing, DePaul University, Chicago, USA

    Bamshad Mobasher

  • Data Miners Inc., Boston, USA

    Brij Masand

  • University of Illinois, Chicago, USA

    Philip S. Yu

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