%0 Journal Article
%A WANG Jia-chun
%A XIAO Bo
%A XU Qian-fang
%T Point-of-Interest Recommendation with Spatio-Temporal Context Awareness
%D 2018
%R 10.13190/j.jbupt.2017-081
%J Journal of Beijing University of Posts and Telecommunications
%P 37-42,50
%V 41
%N 1
%X A personalized hybrid point-of-interest recommendation with spatio-temporal context awareness was proposed to provide users in location-based social networks with superior service. Spatially, two-dimension kernel density estimation was performed for each cluster of check-ins derived by hierarchical clustering and averaged. Meanwhile, random walk on graph was iterated on transition matrices generated from sequence information, location information and social network. The hybrid model combines spatio-temporal context above for recommendation. Experiment on real-world location-based social network(LBSN) datasets demonstrates that the performance metrics of precision and recall of the hybrid recommendation model is superior to other baseline techniques in both standard recommendation scene and cold-start scene.
%U https://journal.bupt.edu.cn/EN/10.13190/j.jbupt.2017-081