Query Processing in Spatial Network Databases

By Dimitris Papadias, Jun Zhang, Nikos Mamoulis, Yufei Tao. Very Large Data Bases Conference, 2003

716 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Voronoi-Based K Nearest Neighbor Search for Spatial Network Databases (2004, methodology): “See the full-paper or [9] for details.”
On Trip Planning Queries in Spatial Databases (2005, methodology): “Spatial databases has been an active area of research in the l ast two decades and many important results in data modeling, spatial indexing, and q uery processing techniques have been reported [29, 17, 40, 37, 42, 26, 36, 4, 18, 27].”
Fast GPU-based locality sensitive hashing for k-nearest neighbor computation (2011, methodology): “Many approaches have been proposed, such as Voronoi-graph based methods [26, 18], Euclidean restriction plus network expansion [34], etc.”
Scalable network distance browsing in spatial databases (2008, methodology): “[21]) is that in our algorithm the shortest paths between the various vertices in the spatial network are only computed once, whereas in the methods that are based on Dijkstra’s algorithm the shortest paths between some vertices are computed repeatedly as the query object and the number of sought ne”