Agents and data mining: mutual enhancement by integration

Authors:
Chengqi Zhang;Zili Zhang;Longbing Cao
Affiliations:
Faculty of Information Technology, University of Technology, Sydney, Broadway, NSW, Australia;Faculty of Computer and Information Science, Southwest China Normal University, Chongqing, China;Faculty of Information Technology, University of Technology, Sydney, Broadway, NSW, Australia
Venue:
AIS-ADM 2005 Proceedings of the 2005 international conference on Autonomous Intelligent Systems: agents and Data Mining
Year:
2005

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Abstract

This paper tells a story of synergism of two cutting edge technologies — agents and data mining. By integrating these two technologies, the power for each of them is enhanced. Integrating agents into data mining systems, or constructing data mining systems from agent perspectives, the flexibility of data mining systems can be greatly improved. New data mining techniques can add to the systems dynamically in the form of agents, while the out-of-date ones can also be deleted from systems at run-time. Equipping agents with data mining capabilities, the agents are much smarter and more adaptable. In this way, the performance of these agent systems can be improved. A new way to integrate these two techniques –ontology-based integration is also discussed. Case studies will be given to demonstrate such mutual enhancement.