Point of Interest Recommendation in Location-Based Social Networks
The application of Location-based social networks has been increased in today’s world rapidly. Thus POI recommendation has become very popular service in this Location- based social networks. Location-Based social networks mainly consist of Point of Interest (POIs) where POIs and the check- in behaviors can be greatly influenced by the following. One is his/her friend and the other is the user’s behavioral habit. This is called social influence. This social influence in the social networks helps the merchant to publicize their quality work and this attracts many users. Each user has their self-interest and thus this affect th recommendation of POI in the social networks. Our paper works on selected list of POIs that has greatest influence on the places to recommend to the users. The main goals of this paper are the target user’s service need, and promote businesses’ locations (POIs). Thus the paper defines a problem for the location promotion using POIs. To solve the optimization problem, the study also uses sub-modular properties. When conducted the comprehensive performance evaluation, the experimental results showed that this method proposed achieves significantly superior POI recommendations.