Agents and Data Mining Interaction [electronic resource] : 4th International Workshop, ADMI 2009, Budapest, Hungary, May 10-15,2009, Revised Selected Papers / edited by Longbing Cao, Vladimir Gorodetsky, Jiming Liu, Gerhard Weiss, Philip S. Yu.

Invited Talks and Papers -- Agents and Data Mining in Bioinformatics: Joining Data Gathering and Automatic Annotation with Classification and Distributed Clustering -- Knowledge-Based Reinforcement Learning for Data Mining -- Ubiquitous Intelligence in Agent Mining -- Agents Based Data Mining and Decision Support System -- Agent-Driven Data Mining -- Agent-Enriched Data Mining Using an Extendable Framework -- Auto-Clustering Using Particle Swarm Optimization and Bacterial Foraging -- A Self-Organized Multiagent System for Intrusion Detection -- Towards Cooperative Predictive Data Mining in Competitive Environments -- Data Mining Driven Agents -- Improving Agent Bidding in Power Stock Markets through a Data Mining Enhanced Agent Platform -- Enhancing Agent Intelligence through Data Mining: A Power Plant Case Study -- A Sequence Mining Method to Predict the Bidding Strategy of Trading Agents -- Agent Mining Applications -- Agent Assignment for Process Management: Pattern Based Agent Performance Evaluation -- Concept Learning for Achieving Personalized Ontologies: An Active Learning Approach -- The Complex Dynamics of Sponsored Search Markets.

This book constitutes the thoroughly refereed post-conference proceedings of the 4th International Workshop on Agents and Data Mining Interaction, ADMI 2009, held in Budapest, Hungary in May 10-15, 2009 as an associated event of AAMAS 2009, the 8th International Joint Conference on Autonomous Agents and Multiagent Systems. The 12 revised papers and 2 invited talks presented were carefully reviewed and selected from numerous submissions. Organized in topical sections on agent-driven data mining, data mining driven agents, and agent mining applications, the papers show the exploiting of agent-driven data mining and the resolving of critical data mining problems in theory and practice; how to improve data mining-driven agents, and how data mining can strengthen agent intelligence in research and practical applications. Subjects that are also addressed are exploring the integration of agents and data mining towards a super-intelligent information processing and systems, and identifying challenges and directions for future research on the synergy between agents and data mining.

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