Applying web personalization techniques in e-government services

Guo, X; Lu, J; Simoff, S

Applying web personalization techniques in e-government services

Guo, X Lu, J

Simoff, S

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Publication Type:: Conference Proceeding
Citation:: AusWeb05: 11th Australasian World Wide Web Conference, 2005
Issue Date:: 2005-12-01

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Field	Value	Language
dc.contributor.author	Guo, X	en_US
dc.contributor.author	Lu, J https://orcid.org/0000-0003-0690-4732	en_US
dc.contributor.author	Simoff, S	en_US
dc.date.issued	2005-12-01	en_US
dc.identifier.citation	AusWeb05: 11th Australasian World Wide Web Conference, 2005	en_US
dc.identifier.uri	http://hdl.handle.net/10453/1753
dc.description.abstract	Many E-commerce websites attempt to develop personalized features to encourage users' repetitive visits. Yet, there is less attention about the applications of personalization technologies in E-government services. In this study, we present a classification of personalization techniques. Also, a novel recommendation approach is proposed to improve the existing techniques by the integration of user-based and item-based collaborative filtering recommendation techniques. A recommender system prototype, named Smart Trade Exhibitions Finder, is developed to help companies choosing the right trade exhibitions. The outcome of this study will have tremendous significance in overcoming the drawback of existing recommendation approaches. © 2005. Xuetao Guo, Jie Lu & Simeon Simoff.	en_US
dc.relation.ispartof	AusWeb05: 11th Australasian World Wide Web Conference	en_US
dc.title	Applying web personalization techniques in e-government services	en_US
dc.type	Conference Proceeding
utslib.for	0804 Data Format	en_US
dc.location.activity	Gold Coast, Australia	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/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Many E-commerce websites attempt to develop personalized features to encourage users' repetitive visits. Yet, there is less attention about the applications of personalization technologies in E-government services. In this study, we present a classification of personalization techniques. Also, a novel recommendation approach is proposed to improve the existing techniques by the integration of user-based and item-based collaborative filtering recommendation techniques. A recommender system prototype, named Smart Trade Exhibitions Finder, is developed to help companies choosing the right trade exhibitions. The outcome of this study will have tremendous significance in overcoming the drawback of existing recommendation approaches. © 2005. Xuetao Guo, Jie Lu & Simeon Simoff.

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http://hdl.handle.net/10453/1753