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Exploiting large-scale check-in data to recommend time-sensitive routes
Proceedings of the ACM SIGKDD International Workshop on Urban Computing - UrbComp '12
Location-based services allow users to perform geo-spatial checkin actions, which facilitates the mining of the moving activities of human beings. This paper proposes to recommend time-sensitive trip routes, consisting of a sequence of locations with associated time stamps, based on knowledge extracted from large-scale check-in data. Given a query location with the starting time, our goal is to recommend a time-sensitive route. We argue a good route should consider (a) the popularity of places,doi:10.1145/2346496.2346506 dblp:conf/kdd/HsiehLL12 fatcat:rufuf66yzrexzfqmcssaepy3pm