Abstract
Multiagent Systems consist of multiple computing elements called agents, which in order to achieve a given objective, can act on their own, react to the inputs, pro-act and cooperate. Data Mining deals with large data. Large data clustering is a data mining activity wherein efficient clustering algorithms select a subset of original dataset as representative patterns. In the current work we propose a multi-agent based clustering scheme that combines multiple agents, each capable of generating a set of prototypes using an independent prototype selection algorithm. Each prototype set is used to predict the labels of unseen data. The results of these agents are combined by another agent resulting in a high classification accuracy. Such a scheme is of high practical utility in dealing with large datasets.
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References
Agogino, A., Tumer, K.: Efficient Agent-Based Clustering Ensembles. In: AAMAS 2006 (2006)
Buccafurri, F., Rosacci, D., Sarne, G.M.L., Ursino, D.: An agent-based hierarchical clustering approach for e-commerce environments. In: Bauknecht, K., Tjoa, A.M., Quirchmayr, G. (eds.) EC-Web 2002. LNCS, vol. 2455, pp. 109–118. Springer, Heidelberg (2002)
Agent-Mining Interaction and Integration(AMII), http://www.agentmining.org
Cochran, W.: Sampling Techniques. John Wiley & Sons, New York (1963)
Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification. John Wiley & Sons, Wiley-interscience (2000)
Gurruzzo, S., Rosaci, D.: Agent Clustering Based on Semantic Negotiation. ACM Trans. on Autonomous and Adaptive Systems (Article 7) 3(2), 7:1–7:40 (2008)
Han, J., Pei, J., Yin, Y.: Mining frequent patterns without candidate generation. In: Proc. of ACM SIGMOD International Conference of Management of Data (SIGMOD 2000), Texas, pp. 1–12 (2000)
Liu, H., Motoda, H. (eds.): Computational Methods in Feature Selection. Chapman & Hall, CRC, FL (2008)
Jain, A.K., Murty, M.N., Flynn, P.J.: Data Clustering: A Review. ACM Computing Review 31(3), 264–323 (1999)
Kittler, J., Hatef, M., Duin, P.W., Matas, J.: On Combining Classifiers. IEEE Trans. on Pattern Analysis and Machine Intelligence 20(3), 226–239 (1998)
Ogston, E., Overreinder, R., van Steen, M., Brazier, F.: A method for decentralizing clustering in large multi-agent systems. In: Proc. of AAMAS 2003, ACM-SIGART, pp. 789–796 (2003)
Ouchiyama, H., Hunag, R., Ma, J.: An Evoluationary Rule-based Multi-agents System. In: Emergent Intelligence of Networked Agents. SCI, vol. 56, pp. 203–215. Springer, Heidelberg (2007)
Park, J., Oh, K.: Multi-Agent Systems for Intelligent Clustering. Proc. of World Academy of Science, Engineering and Technology 11, 97–102 (2006)
Ravindra Babu, T., Narasimha Murty, M., Agrawal, V.K.: On simultaneous selection of prototypes and features in large data. In: Pal, S.K., Bandyopadhyay, S., Biswas, S. (eds.) PReMI 2005. LNCS, vol. 3776, pp. 595–600. Springer, Heidelberg (2005)
Ravindra Babu, T., Narasimha Murty, M., Subrahmanya, S.V.: Multiagent Systems for Large Data Clustering. In: Cao, L. (ed.) Data Mining and Multi-agent Interaction, ch.15, pp. 219–238. Springer, Heidelberg (2009)
Spath, H.: Cluster Analysis - Algorithms for Data Reduction and Classification of Objects. Ellis Horwood Limited., West Sussex (1980)
Weiss, G. (ed.): Multiagent Systems - A modern approach to Distributed Artificial Intelligence. The MIT Press, Cambridge (2000)
Wooldridge, M., Jennings, N.R.: Towards a theory of cooperative problem solving. In: Proc. of the Workshop of Distributed Software Agents and Applications, Denmark, pp. 40–53 (1994)
Zhang, S., Zhang, C., Yan, X.: Post-mining: maintenance of association rules by weighting. Information systems 28, 691–707 (2003)
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Ravindra Babu, T., Narasimha Murty, M., Subrahmanya, S.V. (2010). Multiagent Based Large Data Clustering Scheme for Data Mining Applications. In: An, A., Lingras, P., Petty, S., Huang, R. (eds) Active Media Technology. AMT 2010. Lecture Notes in Computer Science, vol 6335. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15470-6_13
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DOI: https://doi.org/10.1007/978-3-642-15470-6_13
Publisher Name: Springer, Berlin, Heidelberg
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