Abstract
Advancement of location-acquisition technologies with fast development of mobile devices and wireless communication caused a revolution of information. It has been used in location-based social networks (LBSNs), has attracted millions of users to Facebook places, Gowalla, and Foursquare, is an important task to make location recommendations to users, and utilizes user preferences and other information that not only help users explore new places but also make LBSNs more attractive to users. This chapter discusses recommender systems (RS) and its application in different fields like LBSN, big data, and real life. It describes traditional recommendation approaches as well as modern approaches and explains smart community as one of powerful techniques to be used. It also introduces the state-of-art geographical techniques and presents a comparative study of recommendation techniques that can be served as a good guide and a roadmap for research and practice in this area. Finally, the authors discuss measurements and the limitations of RS.
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