Multi-agent system for customer relationship management with SVMs tool

Xiao, Y; Liu, B; Luo, D; Cao, L; Deng, F; Hao, Z

Multi-agent system for customer relationship management with SVMs tool

Xiao, Y Liu, B Luo, D Cao, L

Deng, F Hao, Z

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Publication Type:: Journal Article
Citation:: International Journal of Intelligent Information and Database Systems, 2010, 4 (2), pp. 121 - 136
Issue Date:: 2010-04-01

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Field	Value	Language
dc.contributor.author	Xiao, Y	en_US
dc.contributor.author	Liu, B	en_US
dc.contributor.author	Luo, D	en_US
dc.contributor.author	Cao, L https://orcid.org/0000-0003-1562-9429	en_US
dc.contributor.author	Deng, F	en_US
dc.contributor.author	Hao, Z	en_US
dc.date.issued	2010-04-01	en_US
dc.identifier.citation	International Journal of Intelligent Information and Database Systems, 2010, 4 (2), pp. 121 - 136	en_US
dc.identifier.issn	1751-5858	en_US
dc.identifier.uri	http://hdl.handle.net/10453/15096
dc.description.abstract	In this paper, we introduce multiple agents, knowledge discovery and data mining into customer relationship management (CRM) to set up the architecture of a multi-agent-based CRM system (MAB-CRM), and then use the SVMs-based approach to build up the decision support model which can classify the patterns obtained by the multiple agents into several decision levels, so that managers can pursue different decision-making activities according to the decision level of a pattern. Substantial experiments in the two-dimensional space show how the SVMs-based approach works. The practical problem from one Chinese company has been resolved by the SVMs-based approach. The results illustrate that this approach has an effective ability to learn the decision rules from the assessors' experience. Copyright © 2010 Inderscience Enterprises Ltd.	en_US
dc.relation.ispartof	International Journal of Intelligent Information and Database Systems	en_US
dc.relation.isbasedon	10.1504/IJIIDS.2010.032438	en_US
dc.title	Multi-agent system for customer relationship management with SVMs tool	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	4	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	0804 Data Format	en_US
utslib.for	0806 Information Systems	en_US
dc.location.activity	ISI:000249591000002
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre
utslib.copyright.status	closed_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	4	en_US

Abstract:

In this paper, we introduce multiple agents, knowledge discovery and data mining into customer relationship management (CRM) to set up the architecture of a multi-agent-based CRM system (MAB-CRM), and then use the SVMs-based approach to build up the decision support model which can classify the patterns obtained by the multiple agents into several decision levels, so that managers can pursue different decision-making activities according to the decision level of a pattern. Substantial experiments in the two-dimensional space show how the SVMs-based approach works. The practical problem from one Chinese company has been resolved by the SVMs-based approach. The results illustrate that this approach has an effective ability to learn the decision rules from the assessors' experience. Copyright © 2010 Inderscience Enterprises Ltd.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/15096