Personalized Point of Interest Recommendation Using Check-In History and Friend's Interest

With the popularity of location based social networks, check-in activity has increased tremendously and that has resulted in research in point of interest recommendation. Point of interest recommendation recommends new places to user when he checks in at a location. In the proposed system, we develop a personalized point of interest recommendation system by considering user preferences which are obtained from user's check in history. Also location popularity and other users' preference are considered when user visits new location. Friend's check-in history is used to give recommendations. Using hybrid approach along with tag and location correlation gives accurate point of interest recommendations.