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Reseach Article

Integration and Interaction of Distributed Data Mining with Agent Technology

Published on May 2012 by Meenu Gupta, Sujit Kumar Singh, Jitender
National Workshop-Cum-Conference on Recent Trends in Mathematics and Computing 2011
Foundation of Computer Science USA
RTMC - Number 10
May 2012
Authors: Meenu Gupta, Sujit Kumar Singh, Jitender
fe7c4aea-f002-49fd-90f2-b4810e91be36

Meenu Gupta, Sujit Kumar Singh, Jitender . Integration and Interaction of Distributed Data Mining with Agent Technology. National Workshop-Cum-Conference on Recent Trends in Mathematics and Computing 2011. RTMC, 10 (May 2012), 36-40.

@article{
author = { Meenu Gupta, Sujit Kumar Singh, Jitender },
title = { Integration and Interaction of Distributed Data Mining with Agent Technology },
journal = { National Workshop-Cum-Conference on Recent Trends in Mathematics and Computing 2011 },
issue_date = { May 2012 },
volume = { RTMC },
number = { 10 },
month = { May },
year = { 2012 },
issn = 0975-8887,
pages = { 36-40 },
numpages = 5,
url = { /proceedings/rtmc/number10/6697-1090/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Workshop-Cum-Conference on Recent Trends in Mathematics and Computing 2011
%A Meenu Gupta
%A Sujit Kumar Singh
%A Jitender
%T Integration and Interaction of Distributed Data Mining with Agent Technology
%J National Workshop-Cum-Conference on Recent Trends in Mathematics and Computing 2011
%@ 0975-8887
%V RTMC
%N 10
%P 36-40
%D 2012
%I International Journal of Computer Applications
Abstract

In recent years, more and more researchers have been involved in research on both agent technology and distributed data mining. A clear disciplinary effort has been activated toward removing the boundary between them, that is the interaction and integration between agent technology and distributed data mining. We refer this to agent mining as a new area. The marriage of agents and distributed data mining is driven by challenges faced by both communities, and the need of developing more advanced intelligence, information processing and systems. In this paper presents an overall picture of agent mining from the perspective of positioning it as an emerging area. We summarize the main distributed data mining, driving forces, disciplinary framework, applications, and trends and directions, data mining-driven agents, and mutual issues in agent mining. Arguably, we draw the following conclusions: (1) agent mining emerges as a new area in the scientific family, (2) both agent technology and distributed data mining can greatly benefit from agent mining, (3) it is very promising to result in additional advancement in intelligent information processing and systems. However, as a new open area, there are many issues waiting for research and development from theoretical, technological and practical perspectives.

References
  1. Aciar, S. , Zhang, D. , Simoff, S. , and Debenham, J. : Informed Recommender Agent: Utilizing Consumer Product Reviews through Text Mining. Proceedings of IADM2006. IEEE Computer Society (2006)
  2. Batik's. , Cho, J. , and Bala, J. : Performance Evaluation of an Agent Based Distributed Data Mining System. Advances in Artificial Intelligence, Volume 3501/2005 (2005)
  3. Cory, J. , Butz, Nguyen, N. , Takama, Y. , Cheung, W. , and Cheung, Y. : Proceedings of IADM2006 (Chaired by Longbing Cao, Zili Zhang, Vladimir Samoilov) in WI-IAT2006 Workshop Proceedings. IEEE Computer Society (2006)
  4. Cao, L. , Wang, J. , Lin, l. , and Zhang, C. : Agent Services-Based Infrastructure for Online Assessment of Trading Strategies. Proceedings of IAT'04, 345-349 (2004).
  5. Cao, L. :Integration of Agents and Data Mining. Technical report, 25 June (2005). http://wwwstaff. it. uts. edu. au/ lbcao/publication/publications. htm.
  6. Cao, L. , Luo, C. and Zhang, C. : Agent-Mining Interaction: An Emerging Area. AIS-ADM, 60-73 (2007).
  7. Cao, L. , Luo, D. , Xiao, Y. and Zheng, Z. Agent Collaboration for Multiple Trading Strategy Integration. KES-AMSTA, 361-370 (2008).
  8. Cao, L. :Agent-Mining Interaction and Integration Topics of Research and Development. http://www. agentmining. org/
  9. Cao, L. : Data Mining and Multiagent Integration. Springer (2009).
  10. Cao, L. and Zhang, C. F-trade: An Agent-Mining Symbiont for Financial Services. AAMAS 262 (2007).
  11. Cao, L. , Yu, P. , Zhang, C. and Zhao, Y. Domain Driven Data Mining. Springer (2009).
  12. Cao, L. , Gorodetsky, V. and Mitkas, P. Agent Mining: The Synergy of Agents and Data Mining. IEEE Intelligent Systems (2009).
  13. . Cao, L. Integrating Agent, Service and Organizational Computing. International Journal of Software Engineering and Knowledge Engineering, 18(5): 573-596 (2008)
  14. . Cao, L. and He, T. Developing Actionable Trading Agents. Knowledge and Information Systems: An International Journal, 18(2): 183-198 (2009).
  15. . Cao, L. Developing Actionable Trading Strategies, Knowledge Processing and Decision Making in Agent Based Systems, 193-215, Springer (2008).
  16. . Cao, L. , Zhang, Z. , Gorodetsky, V. and Zhang, C. . Editor's Introduction: Interaction between Agents and Data Mining, International Journal of Intelligent Information and Database Systems, Inderscience, 2(1): 1-5 (2008).
  17. . Cao, L. , Gorodetsky, V. and Mitkas, P. Editorial: Agents and Data Mining. IEEE Intelligent Systems (2009).
  18. . Cao, L. Agent & Data Mining Interaction, Tutorial for 2007 IEEE/WIC/ACM Joint Conferences on Web Intelligence and Intelligent Agent Technology (2007).
  19. . Cao, L. , Zhang, C. and Zhang, Z. Agents and Data Mining: Interaction and Integration, Taylor & Francis (2010).
  20. . Brazdil, P. , and Muggleton, S. : Learning to Relate Terms in a Multiple Agent Environment. EWSL91 (1991)
  21. . Davies, W. : ANIMALS: A Distributed, Heterogeneous Multi-Agent Learning System. MSc Thesis, University of Aberdeen (1993)
  22. . Davies, W. : Agent-Based Data-Mining (1994)
  23. . Edwards, P. , and Davies, W. : A Heterogeneous Multi-Agent Learning System. In Deen, S. M. (ed) Proceedings of the Special Interest Group on Cooperating Knowledge Based Systems. University of Keele (1993) 163-184.
  24. . Gorodetsky, V. , Liu, J. , Skormin, V. A. : Autonomous Intelligent Systems: Agents and Data Mining book. Lecture Notes in Computer Science Volume 3505 (2005)
  25. . Gorodetsky, V. ; Karsaev, O. and Samoilov, V. : Multi-Agent Technology for Distributed Data Mining and Classification. IAT 2003. (2003) 438 - 441
  26. . Gorodetsky, V. , Karsaev, O. and Samoilov, V. : Infrastructural Issues for Agent-Based Distributed Learning. Proceedings of IADM2006, IEEE Computer Society Press
  27. . Han, J. , and Kamber, M. : Data Mining: Concepts and Techniques (2nd version). Morgan Kaufmann (2006)
  28. . Kaya, M. and Alhajj, R. : A Novel Approach to Multi-Agent Reinforcement Learning: Utilizing OLAP Mining in the Learning Process. IEEE Transactions on Systems, Man and Cybernetics, Part C, Volume 35, Issue 4 (2005) 582 - 590
  29. . Kaya, M. and Alhajj, R. : Fuzzy OLAP Association Rules Mining-Based Modular Reinforcement Learning Approach for Multi-Agent Systems. IEEE Transactions on Systems, Man and Cybernetics, Part B, Volume 35, Issue 2, (2005) 326 - 338
  30. . Klusch, M. , Lodi, S. and Gianluca, M. : The Role of Agents in Distributed Data Mining: Issues and Benefits. Intelligent Agent Technology (2003): 211 - 217
  31. . Klusch, M. , Lodi, S. and Moro,G. : Agent-Based Distributed Data Mining: The KDEC Scheme. Intelligent Information Agents: The AgentLink Perspective Volume 2586 (2003) Lecture Notes in Computer Science
  32. . Klusch, M. , Lodi, S. and Moro,G. : Issues of Agent-Based Distributed Data Mining. Proceedings of AAMAS, ACM Press (2003)
Index Terms

Computer Science
Information Sciences

Keywords

Distributed Data Mining ddm multi-agent System (mas) Distributed Artificial Intelligence (dai)