Advances in Web Mining and Web Usage Analysis (eBook, PDF)
7th International Workshop on Knowledge Discovery on the Web, WEBKDD 2005, Chicago, IL, USA, August 21, 2005, Revised Papers Redaktion: Nasraoui, Olfa; Yu, Philip; Masand, Brij; Mobasher, Manshad; Spiliopoulou, Myra; Zaiane, Osmar
Advances in Web Mining and Web Usage Analysis (eBook, PDF)
7th International Workshop on Knowledge Discovery on the Web, WEBKDD 2005, Chicago, IL, USA, August 21, 2005, Revised Papers Redaktion: Nasraoui, Olfa; Yu, Philip; Masand, Brij; Mobasher, Manshad; Spiliopoulou, Myra; Zaiane, Osmar
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This book constitutes the thoroughly refereed post-proceedings of the 7th International Workshop on Mining Web Data, WEBKDD 2005, held in Chicago, IL, USA in August 2005 in conjunction with the 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2005. The nine revised full papers presented together with a detailed preface went through two rounds of reviewing and improvement and were carefully selected for inclusion in the book.
This book constitutes the thoroughly refereed post-proceedings of the 7th International Workshop on Mining Web Data, WEBKDD 2005, held in Chicago, IL, USA in August 2005 in conjunction with the 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2005. The nine revised full papers presented together with a detailed preface went through two rounds of reviewing and improvement and were carefully selected for inclusion in the book.
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Autorenporträt
Olfa Nasraoui, University of Louisville, KY, USA / Osmar Zaiane, University of Alberta, AB, Canada / Myra Spiliopoulou, Otto-von-Guericke-University, Magdeburg, Germany / Manshad Mobasher, DePaul University, Chicago, IL, USA / Brij Masand, Data Miners, Inc., Boston, MA, USA / Philip Yu, IBM T.J. Watson, Yorktown Heights, NY, USA
Inhaltsangabe
Mining Significant Usage Patterns from Clickstream Data.- Using and Learning Semantics in Frequent Subgraph Mining.- Overcoming Incomplete User Models in Recommendation Systems Via an Ontology.- Data Sparsity Issues in the Collaborative Filtering Framework.- USER: User-Sensitive Expert Recommendations for Knowledge-Dense Environments.- Analysis and Detection of Segment-Focused Attacks Against Collaborative Recommendation.- Adaptive Web Usage Profiling.- On Clustering Techniques for Change Diagnosis in Data Streams.- Personalized Search Results with User Interest Hierarchies Learnt from Bookmarks.
Mining Significant Usage Patterns from Clickstream Data.- Using and Learning Semantics in Frequent Subgraph Mining.- Overcoming Incomplete User Models in Recommendation Systems Via an Ontology.- Data Sparsity Issues in the Collaborative Filtering Framework.- USER: User-Sensitive Expert Recommendations for Knowledge-Dense Environments.- Analysis and Detection of Segment-Focused Attacks Against Collaborative Recommendation.- Adaptive Web Usage Profiling.- On Clustering Techniques for Change Diagnosis in Data Streams.- Personalized Search Results with User Interest Hierarchies Learnt from Bookmarks.
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