DocumentCode :
920353
Title :
Agent Mining: The Synergy of Agents and Data Mining
Author :
Cao, Longbing ; Gorodetsky, Vladimir ; Mitkas, Pericles A.
Author_Institution :
Univ. of Technol., Sydney, NSW
Volume :
24
Issue :
3
fYear :
2009
Firstpage :
64
Lastpage :
72
Abstract :
Autonomous agents and multiagent systems (or agents) and data mining and knowledge discovery (or data mining) are two of the most active areas in information technology. Ongoing research has revealed a number of intrinsic challenges and problems facing each area, which can´t be addressed solely within the confines of the respective discipline. A profound insight of bringing these two communities together has unveiled a tremendous potential for new opportunities and wider applications through the synergy of agents and data mining. With increasing interest in this synergy, agent mining is emerging as a new research field studying the interaction and integration of agents and data mining. In this paper, we give an overall perspective of the driving forces, theoretical underpinnings, main research issues, and application domains of this field, while addressing the state-of-the-art of agent mining research and development. Our review is divided into three key research topics: agent-driven data mining, data mining-driven agents, and joint issues in the synergy of agents and data mining. This new and promising field exhibits a great potential for groundbreaking work from foundational, technological and practical perspectives.
Keywords :
data mining; multi-agent systems; agent mining; agent-driven data mining; autonomous agents; data mining-driven agents; information technology; knowledge discovery; multiagent systems; Communities; Data mining; Delta modulation; Enterprise resource planning; Humans; Intelligent agent; Intelligent systems; Logic; Multiagent systems; Peer to peer computing; artificial intelligence; autonomous agents; data mining; knowledge discovery; multi-agent systems;
fLanguage :
English
Journal_Title :
Intelligent Systems, IEEE
Publisher :
ieee
ISSN :
1541-1672
Type :
jour
DOI :
10.1109/MIS.2009.45
Filename :
4983383
Link To Document :
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