Agents and Data Mining Interaction

  • Cao L
  • Gorodetsky V
  • Liu J
  • et al.
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Abstract

Agent-based workflow has been proven its potential in overcoming issues in traditional workflow-based systems, such as decentralization, organizational issues, etc. The existing data mining tools provide workflow metaphor for data mining process visualization, audition and monitoring; these are particularly useful for distributed environments. In agent-based distributed data mining (ADDM), agents are an integral part of the system and can seamlessly incorporate with workflows. We describe a mechanism to use workflow in descriptive and executable styles to incorporate between workflow generators and executors. This paper shows that agent-based workflows can improve ADDM interoperability and flexibility, and also demonstrates the concepts and implementation with a supporting the argument, a multi-agent architecture and an agent-based workflow model are demonstrated.

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Cao, L., Gorodetsky, V., Liu, J., Weiss, G., & Yu, P. S. (2009). Agents and Data Mining Interaction. (L. Cao, V. Gorodetsky, J. Liu, G. Weiss, & P. S. Yu, Eds.), Agents and Data Mining Interaction (Vol. 5680, p. 198). Berlin, Heidelberg: Springer Berlin Heidelberg. Retrieved from http://link.springer.com/10.1007/978-3-642-03603-3

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