Recommended into the location-based social networking users places of interest

The use of location-based social networks is increasing day by day. The purpose of the use of social networks is not only to communicate and share photos but also to report the locations of places and places where they are located. Recommendation systems are used according to the location notifications. The aim of this thesis is to recommend places suitable for users' preferences by using a recommendation system based on link prediction. Predictions are made by taking into account the past check-in information and hometown information of the users. These predictions are made using the link estimation method in a two-part network. Supervised learning algorithms were applied to the obtained data set. The experimental results conducted on real data showed the feasibility of the method and achieved high performance in terms of performance criteria such as accuracy and F-measure.