Recommending Trade Exhibitions by Integrating Semantic Information with Collaborative Filtering

Abstract

Recommender systems have gained successfully applications for the past ten years, particular in E-commerce domain. However, existing recommendation approaches can not effectively deal with recommendation issue of one-and-only items occurred in government-to-business services, e.g. recommendation of trade exhibitions. Thus, in this study, we propose a novel approach by integrating semantic information with the traditional item-based collaborative filtering, and attempt to help the businesses choose the right trade exhibitions at the right time. The outcome of this study will have tremendous significance in overcoming the ýnew itemý problem of existing recommendation approaches.