Voronoi-based multi-level range search in mobile navigation
Multimedia Tools and Applications
Optimized skyline queries on road networks using nearest neighbors
Personal and Ubiquitous Computing
Continuous reverse k nearest neighbors queries in Euclidean space and in spatial networks
The VLDB Journal — The International Journal on Very Large Data Bases
Efficiently processing snapshot and continuous reverse k nearest neighbors queries
The VLDB Journal — The International Journal on Very Large Data Bases
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One of the problems that arise in geographical information systems is finding objects that are influenced by other objects. While most research focuses on kNN (k Nearest Neighbor) and RNN (Reverse Nearest Neighbor) queries, an important type of proximity queries called Reverse Farthest Neighbor (RFN) has not received much attention. Since our previous work shows that kNN and RNN queries in spatial network databases can be efficiently solved using Network Voronoi Diagram (NVD), in this paper, we aim to introduce a new approach to process reverse proximity queries including RFN and RkNN/RkFN queries. Our approach is based on NVD and pre-computation of network distances, and is applicable for spatial road network maps. Being the most fundamental Voronoi-based approach for RFN and RkNN/RkFN queries, our solutions show that they can be efficiently used for networks that have a low and medium level of density.