Agents and Data Mining Interaction

1. Front Matter

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2. Invited Talks and Papers

   1. Front Matter

      Pages 1-1

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   2. Agents and Data Mining in Bioinformatics: Joining Data Gathering and Automatic Annotation with Classification and Distributed Clustering

      • Ana L. C. Bazzan

      Pages 3-20

   3. Knowledge-Based Reinforcement Learning for Data Mining

      • Daniel Kudenko, Marek Grzes

      Pages 21-22

   4. Ubiquitous Intelligence in Agent Mining

      • Longbing Cao, Dan Luo, Chengqi Zhang

      Pages 23-35

   5. Agents Based Data Mining and Decision Support System

      • Serge Parshutin, Arkady Borisov

      Pages 36-49

3. Agent-Driven Data Mining

   1. Front Matter

      Pages 51-51

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   2. Agent-Enriched Data Mining Using an Extendable Framework

      • Kamal Ali Albashiri, Frans Coenen

      Pages 53-68

   3. Auto-Clustering Using Particle Swarm Optimization and Bacterial Foraging

      • Jakob R. Olesen, Jorge Cordero H., Yifeng Zeng

      Pages 69-83

   4. A Self-Organized Multiagent System for Intrusion Detection

      • Esteban J. Palomo, Enrique Domínguez, Rafael M. Luque, Jose Muñoz

      Pages 84-94

   5. Towards Cooperative Predictive Data Mining in Competitive Environments

      • Viliam Lisý, Michal Jakob, Petr Benda, Štěpán Urban, Michal Pěchouček

      Pages 95-108

4. Data Mining Driven Agents

   1. Front Matter

      Pages 109-109

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   2. Improving Agent Bidding in Power Stock Markets through a Data Mining Enhanced Agent Platform

      • Anthony C. Chrysopoulos, Andreas L. Symeonidis, Pericles A. Mitkas

      Pages 111-125

   3. Enhancing Agent Intelligence through Data Mining: A Power Plant Case Study

      • Christina Athanasopoulou, Vasilis Chatziathanasiou

      Pages 126-138

   4. A Sequence Mining Method to Predict the Bidding Strategy of Trading Agents

      • Vivia Nikolaidou, Pericles A. Mitkas

      Pages 139-151

5. Agent Mining Applications

   1. Front Matter

      Pages 153-153

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   2. Agent Assignment for Process Management: Pattern Based Agent Performance Evaluation

      • Stefan Jablonski, Ramzan Talib

      Pages 155-169

   3. Concept Learning for Achieving Personalized Ontologies: An Active Learning Approach

      • Murat Şensoy, Pinar Yolum

      Pages 170-182

   4. The Complex Dynamics of Sponsored Search Markets

      • Valentin Robu, Han La Poutré, Sander Bohte

      Pages 183-198

6. Back Matter

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The2009InternationalWorkshoponAgentsandDataMiningInteraction(ADMI 2009) was a joint event with AAMAS2009. In recentyears,agents and data mining interaction (ADMI), or agent mining forshort,hasemergedasaverypromisingresearch?eld. Followingthesuccessof ADMI 2006 in Hong Kong, ADMI 2007 in San Jose, and ADMI 2008 in Sydney, the ADMI 2009 workshop in Budapest provided a premier forum for sharing research and engineering results, as well as potential challenges and prospects encountered in the synergy between agents and data mining. As usual, the ADMI workshop encouraged and promoted theoretical and applied research and development, which aims at: – Exploitingagent-drivendatamininganddemonstratinghowintelligentagent technology can contribute to critical data mining problems in theory and practice – Improving data mining-driven agents and showing how data mining can strengthen agent intelligence in research and practical applications – Exploring the integration of agents and data mining toward a super-intelligent information processing and systems – Identifying challenges and directions for future research on the synergy between agents and data mining ADMI 2009 featured two invited talks and twelve selected papers. The ?rst invited talk was on “Agents and Data Mining in Bioinformatics,” with the s- ond focusing on “Knowledge-Based Reinforcement Learning. ” The ten accepted papers are from seven countries. A majority of submissions came from Eu- pean countries, indicating the boom of ADMI research in Europe. In addition the two invited papers, addressed fundamental issues related to agent-driven data mining, data mining-driven agents, and agent mining applications. The proceedings of the ADMI workshops will be published as part of the LNAIseriesbySpringer.WeappreciatethesupportofSpringer,andinparticular Alfred Hofmann.

• agent architectures
• agent assignment
• agent interaction
• agent systems implementation
• agent technology
• agent-based simulation
• agents
• autonomous agent
• autonomous agents
• business benefit
• classifier generation
• collaborative filtering
• community detection
• complex systems
• data mining

• Faculty of IT, University of Technology, Sydney, Australia

  Longbing Cao

• St. Petersburg Intitute for Informaticsand Automation, St. Petersburg, Russia

  Vladimir Gorodetsky

• Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong, Hong Kong

  Jiming Liu

• Software Competence Center Hagenberg GmbH, Hagenberg, Austria

  Gerhard Weiss

• Department of Computer Science, University of Illinois at Chicago, Chicago, USA

  Philip S. Yu

Policies and ethics