A Framework of Hybrid Recommendation System for Government-to-Business Personalized E-Services

Abstract

One of the challenges facing e-governments is how to provide businesses with services and information specific to their needs, rather than an undifferentiated mass of information. One way to achieve this is through the design and development of personalized government e-services using recommendation systems. To this purpose, this study presents a personalized hybrid recommender system framework to handle personalized recommendations in G2B e-services, in particular, business partner matching e-services. The proposed framework employs a hybrid trust-based multi-criteria recommendation model which integrates the techniques of trust-based filtering with the multi-criteria CF. The proposed system can be used to reduce the time, cost and risk of businesses involved in entering international markets and thus improve the quality of G2B e-services.