Abstract: Recommendation systems help users with convenient access to the products and services they might be interested in the real world. Due to the needs of effective prediction and efficient recommendation, it is beneficial for the location-based services (LBS), to find out the userís next movable location that the user might visit. So in this paper, different types of approaches used to find, predict, and analyze location based services are discussed. The service prediction based on the implicit and explicit feedback is a trending one. It is necessary to deploy those prediction and recommendation services for real-time mobile application with trajectory mapping. While considering location informationís, then the data size became huge and dynamic. Finding optimal solution to predict the rating based on the location and explicit behavior is surveyed. At last the suggestions for further process also given in this paper.
Keywords: Big data, Geographical location, Recommender systems, Web mining, social network services, Rating prediction, Predictive models, Point of Interest.