Advances in Web Mining and Web Usage Analysis

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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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.

• 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

• 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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