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Agent-Mining Interaction: An Emerging Area.

Authors :
Carbonell, Jaime G.
Siekmann, Jörg
Gorodetsky, Vladimir
Skormin, Victor A.
Cao, Longbing
Luo, Chao
Zhang, Chengqi
Source :
Autonomous Intelligent Systems: Multi-Agents & Data Mining; 2007, p60-73, 14p
Publication Year :
2007

Abstract

In the past twenty years, agents (we mean autonomous agent and multi-agent systems) and data mining (also knowledge discovery) have emerged separately as two of most prominent, dynamic and exciting research areas. In recent years, an increasingly remarkable trend in both areas is the agent-mining interaction and integration. This is driven by not only researcher's interests, but intrinsic challenges and requirements from both sides, as well as benefits and complementarity to both communities through agent-mining interaction. In this paper, we draw a high-level overview of the agent-mining interaction from the perspective of an emerging area in the scientific family. To promote it as a newly emergent scientific field, we summarize key driving forces, originality, major research directions and respective topics, and the progression of research groups, publications and activities of agent-mining interaction. Both theoretical and application-oriented aspects are addressed. The above investigation shows that the agent-mining interaction is attracting everincreasing attention from both agent and data mining communities. Some complicated challenges in either community may be effectively and efficiently tackled through agent-mining interaction. However, as a new open area, there are many issues waiting for research and development from theoretical, technological and practical perspectives. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540728382
Database :
Supplemental Index
Journal :
Autonomous Intelligent Systems: Multi-Agents & Data Mining
Publication Type :
Book
Accession number :
33213870
Full Text :
https://doi.org/10.1007/978-3-540-72839-9_5