Context-Aware Group Recommendation for Point-of-Interests

Group recommendation generates a ranked list of recommendations for a group of users. Point-of-interests (POIs) group recommendation aims to suggest the most agreeable meeting places for a group of users. Although there are a lot of studies on group recommendation for POIs, few studies take into account the rationality of location for the whole group. In this paper, we propose a novel POI group recommendation method which factors into the rationality of the location and the intra-group influence when making group decisions. We take into account the importance of location in POI recommendations and employ distance-based pre-filtering and distance-based ranking adjustment to improve recommendation satisfaction. We have conducted extensive experimental evaluations of the proposed method via a realworld data set, which is prepared from 1 375 024 Beijing POI comment records hosted by a review website. Comprehensive experimental results show that our proposed POI group recommendation method outperforms other representative ones in terms of global satisfaction and distance satisfaction, even in the context of individual recommendation.