A Signed Trust-Based Recommender Approach for Personalized Government-to-Business e-Services

Mao, M; Zhang, G; Lu, J; Zhang, J

A Signed Trust-Based Recommender Approach for Personalized Government-to-Business e-Services

Mao, M Zhang, G

Lu, J

Zhang, J

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Publication Type:: Conference Proceeding
Citation:: Advances in Intelligent Systems and Computing, 2014, 214 pp. 91 - 101
Issue Date:: 2014-01-01

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Field	Value	Language
dc.contributor.author	Mao, M	en_US
dc.contributor.author	Zhang, G https://orcid.org/0000-0003-3960-0583	en_US
dc.contributor.author	Lu, J https://orcid.org/0000-0003-0690-4732	en_US
dc.contributor.author	Zhang, J	en_US
dc.date.issued	2014-01-01	en_US
dc.identifier.citation	Advances in Intelligent Systems and Computing, 2014, 214 pp. 91 - 101	en_US
dc.identifier.issn	2194-5357	en_US
dc.identifier.uri	http://hdl.handle.net/10453/37418
dc.description.abstract	Recently recommender systems are introduced into the web-based government applications which expect to provide personalized Government-to-Business (G2B) e-Services. For more personalization, we illustrate a subjective signed trust relationship between users, and based on such trust we proposed a recommendation framework for G2B e-services. A case study is conducted as an example of implementing our approach in e-government applications. Empirical analysis is also conducted to compare our approach with other models, which shows that our approach is of the highest. In conclusion, the signed trust relationship can reflect the real preferences of users, and the proposed recommendation framework is believed to be reliable and applicable. © Springer-Verlag Berlin Heidelberg 2014.	en_US
dc.relation.ispartof	Advances in Intelligent Systems and Computing	en_US
dc.relation.isbasedon	10.1007/978-3-642-37832-4_9	en_US
dc.title	A Signed Trust-Based Recommender Approach for Personalized Government-to-Business e-Services	en_US
dc.type	Conference Proceeding
utslib.citation.volume	214	en_US
utslib.for	080105 Expert Systems	en_US
utslib.for	080605 Decision Support and Group Support Systems	en_US
utslib.for	080108 Neural, Evolutionary and Fuzzy Computation	en_US
dc.location.activity	Beijing, China
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 Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	214	en_US

Abstract:

Recently recommender systems are introduced into the web-based government applications which expect to provide personalized Government-to-Business (G2B) e-Services. For more personalization, we illustrate a subjective signed trust relationship between users, and based on such trust we proposed a recommendation framework for G2B e-services. A case study is conducted as an example of implementing our approach in e-government applications. Empirical analysis is also conducted to compare our approach with other models, which shows that our approach is of the highest. In conclusion, the signed trust relationship can reflect the real preferences of users, and the proposed recommendation framework is believed to be reliable and applicable. © Springer-Verlag Berlin Heidelberg 2014.

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http://hdl.handle.net/10453/37418