Behdad Karimi - Computer Science, Qom University Qom, Qom, Iran
Mohammad Hossein Yektaei - Computer Science, Islamic Azad University of Abadan Abadan, Khozestan, Iran

Recent advances in mobile devices permit the use of geographic data in online social networks based on traditional Web site. Which leads to the formation of location based social networks.One of the services provided in these networks is personal location recommendation. While real-world users follow timepatterns when they visit the places, so far little attention has been taken to role of the time as an influential factor in users decisions.First, we study user‟s behavior based on temporal-spatial patterns and social dimensions of how user‟s friend affects user‟s decision.Then we model the social, geographical and temporal patterns.We provide a model to recommend location to users. The proposed model examine on real world data of online locationsocial network Foursquare. The results show improvements of our model compare to pervious works.

Location recommender systems, Location Based Social network, geo-temporal influence