LAUSR

With advances in geo-positioning technologies and mobile internet, location-based services have attracted much attention, and spatial keyword queries are catching on fast. However, as far as we aware, no prior work considers the temporal information of geo-tagged objects. Temporal information is important in the spatial keyword query because many objects are not always valid. For example, visitors may plan their trips according to the opening time of attractions. In this paper, we identify and solve a novel problem, i.e., the time-aware Boolean spatial keyword query (TABSKQ), which returns the $k$ objects that satisfy users’ spatio-temporal description and textual constraint. We first present pruning strategies and algorithm based on the CIR $^{+}$ -tree (i.e., the CIR-tree with temporal information). Then, we propose an efficient index structure, called the TA-tree, and its corresponding algorithms, which can prune the search space using both spatio-temporal and textual information. Furthermore, we study an interesting TABSKQ variant, i.e., Joint TABSKQ (JTABSKQ), which aims to process a set of TABSKQs jointly, and extend our techniques to tackle it. Extensive experiments with real datasets offer insight into the performance of our proposed indices and algorithms.