Context-aware Location Search on Maps

Location searching by keywords has immense demands in location-based services (LBSs). In this paper, we study the context-aware location search problem based on maps. Specifically, given a primary keyword and a set of contexts keywords as constraints, the objective is to search for the best-fit location that meets the user's requirements. In order to improve the performance of the search process, we propose an index structure to reduce the workload of querying. In particular, we consider max distance among the locations corresponding to the primary keyword and all surrounding contexts keywords. Extensive experiments are conducted on multiple datasets to validate the effectiveness of our proposed index structure and searching algorithm.