SocialTrail: Recommending Social Trajectories from Location-Based Social Networks

Trajectory recommendation plays an important role for travel planning. Most existing systems are mainly designed for spot recommendation without the understanding of the overall trip and tend to utilize homogeneous data only (e.g., geo-tagged images). Furthermore, they focus on the popularity of locations and fail to consider other important factors like traveling time and sequence, etc. In this paper, we propose a novel system that can not only integrate geo-tagged images and check-in data to discover meaningful social trajectories to enrich the travel information, but also take both temporal and spatial factors into consideration to make trajectory recommendation more accurately.