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 Egovernment
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.
