A Location Recommender System for Location-Based Social Networks

Abstract

Location-Based Social media have evolved rapidly during the last decade. Most Social Networks provide a plethora of venues and points of interest, while at the same time, users are able to declare their presence in specific locations (a process often referred to as "check-ins"), to provide ratings about the visited places or even suggest them to their friends. Location recommendations depending on users' needs have been a subject of interest for many researchers, while location prediction schemes have been developed in order to provide user's possible future location. In this paper, we present a method for predicting a user's location based on machine learning techniques. The dataset we used was based on input from a well-known Location-Based Social Network. Prediction results can be used in order to make appropriate suggestions for venues or points of interests to users, based on their interests and social connections. We propose a Probabilistic Neural Network and confirm its superior performance against two other types of neural networks.

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