Advertisement

Multi-Agent System for Spatio Temporal Data Mining

  • I. L. Narasimha Rao
  • A. Govardhan
  • K. Venkateswara Rao
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 249)

Abstract

Spatiotemporal data comprises of states or position for an object, an event in space over time. Huge amount of the data is available in various application areas such as environment monitoring, traffic management, and weather forecast. This data might be collected and stored at various locations at different points of time. Many challenges are posed in analytical processing and mining of such data due to complexity of the spatiotemporal objects and their relationships with each other in both temporal and spatial dimensions. More scalable and practical approach in this context is distributed analysis and mining of the spatiotemporal data.

Multi-Agent System deals with applications which need distributed problem solving. The behavior of the agents is based on the data observed from various distributed sources. Since the agents in multi-agent system are generally distributed and have reactive and proactive characteristic, It is appealing to combine distributed spatiotemporal data mining with multi-agent system.

The core issues and problems in multi-agent distributed spatiotemporal data analysis and mining do not concern specific data mining techniques. Its core issues and problems are related to achieving collaboration in the multi-agent system indented for distributed spatiotemporal data analysis and mining. This paper is intended to describe architecture of multi-agent system for spatiotemporal data mining and identify issues involved in realization of such system and also to review technologies available for developing such system.

Keywords

Spatiotemporal Multi Agent Data mining 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Park, B.-H., Kargupta, H.: Distributed Data Mining: Algorithms, Systems, and Applications. In: Data Mining Handbook, pp. 341–358 (2002)Google Scholar
  2. 2.
    Maalal, S., Addou, M.: A new approach of designing Multi-agent Systems. International Journal of Advanced Computer Science and Applications 2(1), 148–157 (2011)Google Scholar
  3. 3.
    Klusch, M., Lodi, S., Moro, G.: Issues of Agent-Based Distributed Data Mining. In: Proceeding of Second International Joint Conference on Autonomous Agents & Multiagent Systems, AAMAS, Melboune, pp. 1034–1035 (2003)Google Scholar
  4. 4.
    Kargupta, H., Hamzaoglu, I., Stafford, B.: Scalable, Distributed Data Mining – An Agent Architecture. In: Proceedings of KDD 1997, pp. 211–214 (1997)Google Scholar
  5. 5.
    Klush, M., Lodi, S., Moro, G.: The role of Agents in Distributed Data Mining: Issues and Benefits. In: IEEE/WIC International Conference on Intelligent Agent Technology, pp. 211–217 (October 2003)Google Scholar
  6. 6.
    Baazaoui Zghal, H., Faiz, S., Ben Ghezala, H.: A framework for Data Mining Based Multi-agent: An Application to Spatial Data. World Academy of Science, Engineering and Technology, 22–26 (2005)Google Scholar
  7. 7.
    Venkateswara Rao, K., Govardhan, A., Chalapati Rao, K.V.: Spatiotemporal Data Mining: Issues, Tasks and Applications. International Journal of Computer Science and Engineering Survey (IJCSES) 3(1), 39–52 (2012) ISSN: 0976-2760 (online), 0976-3252 (print)Google Scholar
  8. 8.
    Venkateswara Rao, K., Govardhan, A., Chalapati Rao, K.V.: An Architecture Framework for Spatiotemporal Data Mining System. International Journal of Software Engineering & Applications (IJSEA) 3(5), 125–146 (2012) ISSN: 0975 - 9018 (online), 0976-2221 (print )Google Scholar
  9. 9.
    Zhang, Z., et al.: Multiagent System for Distributed Computing, Communication and Data Integration Needs in the Power Industry. IEEE Power Engineering Society Meeting 1, 45–49 (2004)Google Scholar
  10. 10.
    Corchado, J.M., Tapia, D.I., Bajo, J.: A Multi-agent Architecture for Distributed Services and Applications. International Journal of Innovative Computing, Information and Control 8(4), 2453–2476 (2012)Google Scholar
  11. 11.
    Gorodetsky, V., Karsaeyv, O., Samoilov, V.: Multi-agent Technology for Distributed Data Mining and Classification. In: Proceedings of the IEEE/WIC International Conference on Intelligent Technology (2003)Google Scholar
  12. 12.
    Bellifemine, F., Poggi, A., Rimassa, G.: JADE: A FIPA-Compliant Agent Framework. In: Proceedings of the Fourth Conference on the Practical Application of Intelligent Agents and Multi-Agent Technology, pp. 97–108 (April 1999)Google Scholar
  13. 13.
    Dinsoreanu, M., Salomie, I., Pusztai, K.: On the Design of Agent-based Systems using UML and Extensions. In: Proceedings of the 24th International Conference on Information Technology Interfaces, pp. 205–210 (2002)Google Scholar
  14. 14.
    Bauer, B., Odell, J.: UML 2.0 and agents: how to build agent-based systems with the new UML standard. Engineering Applications of Artificial Intelligence 18(2), 141–157 (2005)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • I. L. Narasimha Rao
    • 1
  • A. Govardhan
    • 2
  • K. Venkateswara Rao
    • 3
  1. 1.Department of CSEAurora’s Technological and Research Institute, UppalHyderabadIndia
  2. 2.School of ITJNTUHyderabadIndia
  3. 3.Department of CSECVR College of EngineeringVastunagarIndia

Personalised recommendations