Bamshad Mobasher,
Olfa Nasraoui,
Bing Liu,
Brij Masand
e.a.
Springer Berlin Heidelberg
2006e druk, 2006
9783540471271
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
Specificaties
Paperback, 189 blz.
|
Engels
Springer Berlin Heidelberg |
2006e druk, 2006
ISBN13: 9783540471271
Rubricering
Juridisch
:
Onderdeel van serie
Lecture Notes in Computer Science
Levertijd ongeveer 9 werkdagen
Gratis verzonden
Samenvatting
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.
Specificaties
ISBN13:9783540471271
Taal:Engels
Bindwijze:paperback
Aantal pagina's:189
Uitgever:Springer Berlin Heidelberg
Druk:2006
Hoofdrubriek:Automatisering algemeen, Computer en informatica
Inhoudsopgave
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.
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