Titlebook: Data Mining and Multi-agent Integration; Longbing Cao Book 2009 Springer-Verlag US 2009 AAMAS.Clustering.agent-enriched data mining.algori

Ancestor

The EMADS Extendible Multi-Agent Data Mining Frameworkbuted by many individuals and interacting under decentralized control, to address data mining requests. EMADS is seen both as an end user platform and a research tool. This chapter details the EMADS vision, the associated conceptual framework and the current implementation. Although EMADS may be app

总

A Multiagent Approach to Adaptive Continuous Analysis of Streaming Data in Complex Uncertain Environ-hard optimization problem for general metric spaces and is computationally intractable for real-world problems of practical interest. The primary contribution of this work is a multi-agent method for continuous agglomerative hierarchical clustering of streaming data, and a knowledge-based selforgan

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Multiagent Systems for Large Data Clusteringvast volumes of data is available containing enormous amount of hidden information. Generating abstractions from such large data is a challenging data mining task. Efficient large data clustering schemes are important in dealing with such large data. In the current work we provide two different effi

MOAN

A Multiagent, Multiobjective Clustering Algorithmios involving many agents. This approach is based on independent ant colonies, each one trying to optimize one particular feature objective. The multiobjective clustering process is performed by combining the results of all colonies. Experimental evaluation shows that MACC is able to find better res

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Agent-Based Distributed Data Mining: A Surveyl with complex systems has revealed opportunities to improve distributed data mining systems in a number of ways. This paper surveys the integration of multi-agent system and distributed data mining, also known as agent-based distributed data mining, in terms of significance, system overview, existing systems, and research trends.

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Immortal

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Ibrahima Diarrassouba,Youssouf Hadhbieb. In order to do this, each instance of the system is represented by a software agent, which is in charge of interacting with Web search engines and collaborating with the agents that represent other system instances, thereby using data mining techniques. As a result, SKC manages to build and maintain a network node to share knowledge.