Advances in Web Mining and Web Usage Analysis : 6th International Workshop on Knowledge Discovery on the Web, Webkdd 2004 Seattle, Wa, USA, August 22-25, 2004 Revised Selected Papers

Mobasher, Bamshad (EDT); Nasraoui, Olfa (EDT); Liu, Bing (EDT); Masand, Brij (EDT)

ISBN 10: 3540471278 / ISBN 13: 9783540471271

Editore: Springer, 2006

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Codice articolo 5105369-n

Dati bibliografici

• Titolo: Advances in Web Mining and Web Usage Analysis : 6th International Workshop on Knowledge Discovery on the Web, Webkdd 2004 Seattle, Wa, USA, August 22-25, 2004 Revised Selected Papers
• Editore: Springer
• Data di pubblicazione: 2006
• Lingua: Inglese
• ISBN 10: 3540471278
• ISBN 13: 9783540471271
• Rilegatura: Brossura
• Condizione: New

Descrizione articolo

Riassunto

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.

Contenuti

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.