Agent-based distributed data mining: A survey

Moemeng, C; Gorodetsky, V; Zuo, Z; Yang, Y; Zhang, C

Agent-based distributed data mining: A survey

Moemeng, C Gorodetsky, V Zuo, Z Yang, Y Zhang, C

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Publication Type:: Chapter
Citation:: Data Mining and Multi-Agent Integration, 2009, pp. 47 - 58
Issue Date:: 2009-12-01

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Field	Value	Language
dc.contributor.author	Moemeng, C	en_US
dc.contributor.author	Gorodetsky, V	en_US
dc.contributor.author	Zuo, Z	en_US
dc.contributor.author	Yang, Y	en_US
dc.contributor.author	Zhang, C https://orcid.org/0000-0001-5715-7154	en_US
dc.date.issued	2009-12-01	en_US
dc.identifier.citation	Data Mining and Multi-Agent Integration, 2009, pp. 47 - 58	en_US
dc.identifier.isbn	9781441905215	en_US
dc.identifier.uri	http://hdl.handle.net/10453/11642
dc.description.abstract	Distributed data mining is originated from the need of mining over decentralised data sources. Data mining techniques involving in such complex environment must encounter great dynamics due to changes in the system can affect the overall performance of the system. Agent computing whose aim is to deal 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. © 2009 Springer-Verlag US.	en_US
dc.relation.ispartof	Data Mining and Multi-Agent Integration	en_US
dc.relation.isbasedon	10.1007/978-1-4419-0522-2_3	en_US
dc.title	Agent-based distributed data mining: A survey	en_US
dc.type	Chapter
utslib.for	080109 Pattern Recognition and Data Mining	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/DVC (International)
pubs.organisational-group	/University of Technology Sydney/Strength - ACRI - Australia China Relations Institute
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Distributed data mining is originated from the need of mining over decentralised data sources. Data mining techniques involving in such complex environment must encounter great dynamics due to changes in the system can affect the overall performance of the system. Agent computing whose aim is to deal 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. © 2009 Springer-Verlag US.

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http://hdl.handle.net/10453/11642