The growths of internet, Global Positioning System (GPS) and wireless telecommunication technologies have opened new avenues in potential area of mobile computing called Location Based Services (LBS). Recommendation of personalized information / services in location based services has become an attractive trend for success of businesses. A Recommender System attempts to solve the problem of information overload and provides product and service recommendation based on user profile and preferences. The location of the user is an important information item that can be associated to the existing user profile in order to provide efficient recommendations. Also, easy availability of GPS enabled devices brings a large amount of GPS trajectories representing user's mobile logs. These GPS trajectories can be used to mine interesting patterns about users. We have studied the utility and application of information extracted from user's GPS trajectory data in recommender systems. We conceive that recommendation has an intrinsic social component and therefore this work takes a perspective towards the social aspect in location based recommender systems. In this paper, we are presenting the stateof- the-art research trends, challenges and applications in the area of Location-Based Recommender Systems (LBRS).