Advances in Web Mining and Web Usage Analysis (eBook, PDF)
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This book constitutes the thoroughly refereed post-proceedings of the 6th International Workshop on Mining Web Data, WEBKDD 2004, held in Seattle, WA, USA in August 2004 in conjunction with the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2004. The 11 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.…mehr

Produktbeschreibung
This book constitutes the thoroughly refereed post-proceedings of the 6th International Workshop on Mining Web Data, WEBKDD 2004, held in Seattle, WA, USA in August 2004 in conjunction with the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2004. The 11 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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  • Produktdetails
  • Verlag: Springer-Verlag GmbH
  • Seitenzahl: 189
  • Erscheinungstermin: 17. Oktober 2006
  • Englisch
  • ISBN-13: 9783540471288
  • Artikelnr.: 44128995
Autorenporträt
Bamshad Mobasher, DePaul University, Chicago, IL, USA / Olfa Nasraoui, University of Louisville, KY, USA / Bing Liu, University of Illinois, Chicago, IL, USA / Brij Masand, Data Miners Inc., Boston, MA, USA
Inhaltsangabe
Web Usage Analysis and User Modeling.- Mining Temporally Changing Web Usage Graphs.- Improving the Web Usage Analysis Process: A UML Model of the ETL Process.- Web Personalization and Recommender Systems.- Mission-Based Navigational Behaviour Modeling for Web Recommender Systems.- Complete This Puzzle: A Connectionist Approach to Accurate Web Recommendations Based on a Committee of Predictors.- Collaborative Quality Filtering: Establishing Consensus or Recovering Ground Truth?.- Search Personalization.- Spying Out Accurate User Preferences for Search Engine Adaptation.- Using Hyperlink Features to Personalize Web Search.- Semantic Web Mining.- Discovering Links Between Lexical and Surface Features in Questions and Answers.- Integrating Web Conceptual Modeling and Web Usage Mining.- Boosting for Text Classification with Semantic Features.- Markov Blankets and Meta-heuristics Search: Sentiment Extraction from Unstructured Texts.