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The location based social networking services (LBSNSs) are becoming very popular today. In LBSNSs, such as Foursquare, users can explore their places of interests around their current locations, check in at these places to share their locations with their friends, etc. These check-ins contain rich information and imply human mobility patterns; thus, they can greatly facilitate mining and analysis of local geographic topics driven by users' trajectories. The local geographic topics indicate the potential and intrinsic relations among the locations in accordance with users' trajectories. These relations are useful for users in both location and friend recommendations. In this paper, we focus on exploring the local geographic topics through check-ins in Pittsburgh area in Foursquare. We use the Latent Dirichlet Allocation (LDA) model to discover the local geographic topics from the checkins. We also compare the local geographic topics on weekdays with those at weekends. Our results show that LDA works well in finding the related places of interests.

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In many unmanned aerial vehicle (UAV) applications such as land assessment, search and rescue, and precision agriculture, UAVs are often required to survey multiple spatially distributed regions. To perform these applications, one of the key steps is to plan the path for the UAV to quickly cover all regions. The new path planning problem explored here, which we call the TSP-CPP problem, can be viewed as an integration of the traveling salesman problem (TSP) and the coverage path planning (CPP) problem, which has not been well studied in the literature. In this paper, we conduct a systematic investigation on the TSP-CPP problem. In particular, we first provide a mixed integer programming formulation for this new problem, and then introduce a CPP method for covering a single convex polygonal region. Based on this method, we then develop two approaches to solve the TSP-CPP problem, including 1) a dynamic programming-based exact approach that can find the (near) optimal tour, and 2) a heuristic approach that can generate high-quality tours very efficiently. Through comprehensive theoretical analyses and simulation studies, we demonstrate the optimality and efficiency of the proposed approaches. INDEX TERMS Path planning, traveling salesman problem, coverage path planning, multiple convex polygonal regions, unmanned aerial vehicle, optimal path, heuristic algorithm.

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