A top-k spatial keyword (TkSk) query ranks objects based on the distance to the query location and textual relevance to the query keywords. Several solutions have been proposed for top-k spatial keyword queries. However, most of the studies focus on Euclidean space or only investigate the snapshot queries where both the query and data object are static. A few algorithms study TkSk queries in undirected road networks where each edge is undirected and the distance between two points is the length of the shortest path connecting them. However, TkSk queries have not been thoroughly investigated in directed and dynamic spatial networks where each edge has a particular orientation and its weight changes according to the traffic conditions. Therefore, in this study, we address this problem by presenting a new method, called COSK, for processing continuous top-k spatial keyword queries for moving queries in directed and dynamic road networks. We first propose an efficient framework to process snapshot TkSK queries. Furthermore, we propose a safe-exit-based approach to monitor the validity of the results for moving TkSK queries. Our experimental results demonstrate that COSK significantly outperforms existing techniques in terms of query processing time and communication cost.
Efficient Distance-based Query Processing in Spatial Networks
