Building a Value-Centric e-Government Service Framework Based on a Business Model Perspective
EGOV '08 Proceedings of the 7th international conference on Electronic Government
Web-Based Recommender Systems and User Needs --the Comprehensive View
Proceedings of the 2008 conference on New Trends in Multimedia and Network Information Systems
Role-Based and Service-Oriented Security Management in the E-Government Environment
EGOV '09 Proceedings of the 8th International Conference on Electronic Government
Collaborative filtering with ordinal scale-based implicit ratings for mobile music recommendations
Information Sciences: an International Journal
A framework for delivering personalized e-government services from a citizen-centric approach
Proceedings of the 11th International Conference on Information Integration and Web-based Applications & Services
A fuzzy recommender system for eElections
EGOVIS'10 Proceedings of the First international conference on Electronic government and the information systems perspective
Government-to-business personalized e-services using semantic-enhanced recommender system
EGOVIS'11 Proceedings of the Second international conference on Electronic government and the information systems perspective
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
A trust-semantic fusion-based recommendation approach for e-business applications
Decision Support Systems
A hybrid fuzzy-based personalized recommender system for telecom products/services
Information Sciences: an International Journal
Election candidates fuzzy multi-agent recommender system
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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Information overload is becoming one of the problems that hinder the effectiveness of e-government services. Intelligent e-government services with personalized recommendation techniques can provide a solution for this problem. Existing recommendation approaches have not entirely considered the influences of attributes of various online services and may result in no guarantee of recommendation accuracy. This study proposes a new approach to handle recommendation issues of one-and-only items in e-government services. The proposed approach integrates the techniques of semantic similarity and the traditional item-based collaborative filtering. A recommender system named Smart Trade Exhibition Finder has been developed to implement the proposed recommendation approach. The recommender system can be applied in e-government services to improve the quality of government-to-business online services. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 401–417, 2007.