Applying Web Personalization Techniques in E-government Services

Xuetao Guo, Faculty of Information Technology, University of Technology, Sydney, PO BOX 123, Broadway, NSW 2007, Australia. Email: xguo@it.uts.edu.au

Jie Lu, Faculty of Information Technology, University of Technology, Sydney, PO BOX 123, Broadway, NSW 2007, Australia. Email: jielu@it.uts.edu.au

Simeon Simoff, Faculty of Information Technology, University of Technology, Sydney, PO BOX 123, Broadway, NSW 2007, Australia. Email: simeon@it.uts.edu.au

Keywords

Personalization, Recommender system, E-government, Collaborative filtering

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.