Recommending trade exhibitions by integrating semantic information with collaborative filtering

Recommender systems have gained successfully applications 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 have tremendous significance in overcoming the ´new item´ problem of existing recommendation approaches.