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Computer Science - Artificial Intelligence | Advances in Web Mining and Web Usage Analysis - 6th International Workshop on Knowledge Discovery

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, B., Nasraoui, O., Liu, B., Masand, B. (Eds.)

2006, X, 189 p. Also available online.

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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. The extended papers are subdivided into four general groups: Web usage analysis and user modeling, Web personalization and recommender systems, search personalization, and semantic Web mining. The latter contains also papers from the joint KDD workshop on Mining for and from the Semantic Web, MSW 2004.

Content Level » Research

Keywords » data mining - knowledge - knowledge discovery - modeling - recommender system - semantic web - web mining

Related subjects » Artificial Intelligence - Communication Networks - Database Management & Information Retrieval - General Issues

Table of contents 

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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