Agents and Data Mining Interaction

4th International Workshop, ADMI 2009, Budapest, Hungary, May 10-15,2009, Revised Selected Papers

  • Longbing Cao
  • Vladimir Gorodetsky
  • Jiming Liu
  • Gerhard Weiss
  • Philip S. Yu
Conference proceedings ADMI 2009

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5680)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 5680)

Table of contents

  1. Front Matter
  2. Invited Talks and Papers

  3. Agent-Driven Data Mining

    1. Front Matter
      Pages 51-51
    2. Kamal Ali Albashiri, Frans Coenen
      Pages 53-68
    3. Jakob R. Olesen, Jorge Cordero H., Yifeng Zeng
      Pages 69-83
    4. Esteban J. Palomo, Enrique Domínguez, Rafael M. Luque, Jose Muñoz
      Pages 84-94
    5. Viliam Lisý, Michal Jakob, Petr Benda, Štěpán Urban, Michal Pěchouček
      Pages 95-108
  4. Data Mining Driven Agents

    1. Front Matter
      Pages 109-109
    2. Anthony C. Chrysopoulos, Andreas L. Symeonidis, Pericles A. Mitkas
      Pages 111-125
    3. Christina Athanasopoulou, Vasilis Chatziathanasiou
      Pages 126-138
    4. Vivia Nikolaidou, Pericles A. Mitkas
      Pages 139-151
  5. Agent Mining Applications

    1. Front Matter
      Pages 153-153
    2. Valentin Robu, Han La Poutré, Sander Bohte
      Pages 183-198
  6. Back Matter

About these proceedings


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.


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

Editors and affiliations

  • Longbing Cao
    • 1
  • Vladimir Gorodetsky
    • 2
  • Jiming Liu
    • 3
  • Gerhard Weiss
    • 4
  • Philip S. Yu
    • 5
  1. 1.Faculty of ITUniversity of TechnologySydneyAustralia
  2. 2.St. Petersburg Intitute for Informaticsand AutomationSt. PetersburgRussia
  3. 3.Department of Computer ScienceHong Kong Baptist University, Kowloon TongHong KongHong Kong
  4. 4.Software Competence Center Hagenberg GmbHHagenbergAustria
  5. 5.Department of Computer ScienceUniversity of Illinois at ChicagoChicagoUSA

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2009
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-642-03602-6
  • Online ISBN 978-3-642-03603-3
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site