Location Based Place Recommendation using Social Network

In recent times, due to the massive choices on the internet, there is need of the recommender system. It can overcome the information overload problem to convey pertinent information. It gives users the suggestion of items or customized services according to their preferences and past history. Previously, recommender systems were based on demographic, content-based and collaborative filtering. In current time, recommender systems are integrating social information. Recently the online social networks have become very popular on the internet. Due to the increased use of online social network, information exchange has been increased. Users can initiate new relationships with other users based on features such as groups, hobbies and interests. With the help of social network, people can share their visit and check-in information, feelings, views and ideas. As the social network and global positioning system (GPS) technology are growing, location based social networks (LBSNs) are growing rapidly. Location based social networks can offer customized location services to the users with a new point-of-interest (POI). Point-of-interest recommendation can combine location and social network, which integrates online users and physical locations. Point-of-interest recommendation assists users to search new locations as per their preferences or choices. In the recent study of location based social networks, influence factors are taken into consideration. Influence factors like social influence, spatial/geographical influence, temporal influence and popularity features can give better recommendation result. This paper includes the literature survey on recommender system, social network, influence analysis and recommendation of places for location based social networks.