Direction-Aware Top-k Dominating Query

Traditional location-based services (LBSs) only consider the distance of the spatial object w.r.t the user. However, a spatial object has not only the distance attribute but also the direction attribute. In this paper, we propose a new spatial object query, i.e., the direction-aware top-k dominating query (DirDom query). Given a user’s position and his favorite direction, the DirDom query finds the top-k objects with the highest dominant capabilities. The dominant capability of an object is the number of the objects it can dominate. An object can dominate another object if it is better considering both the distance and the direction. Here “better” means it is closer to the user and it is more consistent with the user’s favorite direction. We design R-tree-based algorithms to answer DirDom queries. We evaluate the correctness and the efficiency of the algorithms by using real and synthetic datasets.