A Multi Agent Recommender System that Utilises Consumer Reviews in its Recommendations

Zhang, DD; Simoff, SJ; Aciar, S; Debenham, JK

A Multi Agent Recommender System that Utilises Consumer Reviews in its Recommendations

Zhang, DD Simoff, SJ Aciar, S Debenham, JK

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Publisher:: Inderscience
Publication Type:: Journal Article
Citation:: International Journal of Intelligent Information and Database Systems, 2008, 2 (1), pp. 69 - 81
Issue Date:: 2008-01

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Field	Value	Language
dc.contributor.author	Zhang, DD	en_US
dc.contributor.author	Simoff, SJ	en_US
dc.contributor.author	Aciar, S	en_US
dc.contributor.author	Debenham, JK	en_US
dc.date.issued	2008-01	en_US
dc.identifier.citation	International Journal of Intelligent Information and Database Systems, 2008, 2 (1), pp. 69 - 81	en_US
dc.identifier.issn	1751-5858	en_US
dc.identifier.uri	http://hdl.handle.net/10453/9110
dc.description.abstract	Consumer reviews, opinions and shared experiences in the use of a product form a powerful source of information about consumer preferences that can be used for making recommendations. A novel approach, which utilises this valuable information sources first time to create recommendations in recommender agents was recently developed by Aciar et al. (2007). This paper presents a general framework of this approach. The proposed approach is demonstrated using digital camera reviews as an example.	en_US
dc.publisher	Inderscience	en_US
dc.relation.ispartof	International Journal of Intelligent Information and Database Systems	en_US
dc.title	A Multi Agent Recommender System that Utilises Consumer Reviews in its Recommendations	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.citation.volume	2	en_US
utslib.for	0804 Data Format	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	0806 Information Systems	en_US
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/Faculty of Engineering and Information Technology/School of Software
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Systems, Management and Leadership
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre
utslib.copyright.status	open_access
pubs.consider-herdc	true	en_US
pubs.issue	1	en_US
pubs.volume	2	en_US

Abstract:

Consumer reviews, opinions and shared experiences in the use of a product form a powerful source of information about consumer preferences that can be used for making recommendations. A novel approach, which utilises this valuable information sources first time to create recommendations in recommender agents was recently developed by Aciar et al. (2007). This paper presents a general framework of this approach. The proposed approach is demonstrated using digital camera reviews as an example.

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http://hdl.handle.net/10453/9110