Finding Top-k Places for Group Social Activities
(0) Geo-social network applications utilize check-in information to suggest places for social activities.This paper focuses on recommending points of interest (POIs) to groups of users based on the current location of users and the popularity and suitability of the POIs from history.To address the problem,we propose a new type of query,namely,groupbased geo-social top-k places (GkP) query,which takes spatial proximity and social fitness into consideration.This is among the first attempts,and we present the preliminary results.In particular,we investigate the problem formulation,especially the modeling of spatial proximity and social fitness.Two baseline algorithms,distance-driven and relevancedriven,respectively,are conceived.Initial empirical results confirm that GkP queries meet the needs of potential applications,and the proposed algorithms are sufficient to handle GkP queries.
Xiaosheng Feng Nikos Armenatzoglou Hao Xu Xiang Zhao Pan Hui
National University of Defense Technology,Changsha,China Pivotal Inc.,San Francisco,USA National University of Defense Technology,Changsha,China;Collaborative Innovation Center of Geospati Hong Kong University of Science and Technology,Hong Kong,China
国际会议
International Asia-Pacific Web Conference(第18届国际亚太互联网大会)
苏州
英文
191-203
2016-09-23（万方平台首次上网日期，不代表论文的发表时间）