Collective Spatial Keyword Query on Time Dependent Road Networks

Collective spatial keyword query is an important research in Location Based Services. Existing works only study the problem on Euclidean space and road networks, while in many real-life applications, users pay more attention to the travel time between objects rather than the spatial distance. As the traffic conditions are constantly changing, existing solutions cannot efficiently solve the problem on time dependent road networks. In this paper, we study the problem of collective spatial keyword queries on time dependent road networks (TDCSKQ). We first propose a baseline query algorithm that adopts a filter-verification framework to support TDCSKQ. In the filter phase, we obtain candidate groups. Successively, in the verification phase, we obtain the optimal group. To further improve the efficiency of the algorithm, we present a grid index structure with bitmap. Finally, our experimental results demonstrate the effectiveness and efficiency of the algorithms on real datasets.