Preference Aware Travel Route Recommendation with Temporal Influence

There have been vast advances and rapid growth in Location based social networking (LBSN) services in recent years. Travel route recommendation is one of the most important applications in the LBSN services. Travel route recommendation provides users a sequence of POIs (Point of Interests) as a route to visit. In this paper, we propose to recommend time-aware and preference-aware travel routes consisting of a sequence of POI locations with corresponding time information. It helps users not only to explore interesting locations in a new city, but also it will help to plan the entire trip with those locations with the approximated time information under specific time constraints. First, we find the interesting POI locations that considers the following factors: User's categorical preferences, temporal activities and popularity of location. Then, we propose an efficient solution to generate travel routes with those locations including time to visit each location. These travel routes will inform users where to visit and when to visit. We evaluate the efficiency and effectiveness of our solution on a real life LBSN dataset.