Optimal quadtree construction algorithms
Computer Vision, Graphics, and Image Processing
A population analysis for hierarchical data structures
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Planar graph decomposition and all pairs shortest paths
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SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Storing a collection of polygons using quadtrees
ACM Transactions on Graphics (TOG)
Distance browsing in spatial databases
ACM Transactions on Database Systems (TODS)
An effective way to represent quadtrees
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Efficient Processing of Spatial Queries in Line Segment Databases
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A Branch and Bound Algorithm for Computing k-Nearest Neighbors
IEEE Transactions on Computers
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Voronoi-based K nearest neighbor search for spatial network databases
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Fast algorithms for the all nearest neighbors problem
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The V*-Diagram: a query-dependent approach to moving KNN queries
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Efficient Continuous Nearest Neighbor Query in Spatial Networks Using Euclidean Restriction
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Towards modeling the traffic data on road networks
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Fast shortest path distance estimation in large networks
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Map-matching for low-sampling-rate GPS trajectories
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Path oracles for spatial networks
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Database and Representation Issues in Geographic Information Systems (GIS)
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Probabilistic path queries in road networks: traffic uncertainty aware path selection
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Best point detour query in road networks
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Local network Voronoi diagrams
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Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
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SUMMA: subgraph matching in massive graphs
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On-line preferential nearest neighbor browsing in large attributed graphs
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Efficient k-nearest neighbor search in time-dependent spatial networks
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part I
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Proceedings of the VLDB Endowment
CIM: categorical influence maximization
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Finding shortest path on land surface
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Online computation of fastest path in time-dependent spatial networks
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Context-aware nearest neighbor query on social networks
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Top-K possible shortest path query over a large uncertain graph
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Shortest path and distance queries on road networks: an experimental evaluation
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DNIS'10 Proceedings of the 6th international conference on Databases in Networked Information Systems
Shortest path computation with no information leakage
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A highway-centric labeling approach for answering distance queries on large sparse graphs
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Efficient reachability query evaluation in large spatiotemporal contact datasets
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SMashQ: spatial mashup framework for k-NN queries in time-dependent road networks
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Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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A group based approach for path queries in road networks
SSTD'13 Proceedings of the 13th international conference on Advances in Spatial and Temporal Databases
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An algorithm is presented for finding the k nearest neighbors in a spatial network in a best-first manner using network distance. The algorithm is based on precomputing the shortest paths between all possible vertices in the network and then making use of an encoding that takes advantage of the fact that the shortest paths from vertex u to all of the remaining vertices can be decomposed into subsets based on the first edges on the shortest paths to them from u. Thus, in the worst case, the amount of work depends on the number of objects that are examined and the number of links on the shortest paths to them from q, rather than depending on the number of vertices in the network. The amount of storage required to keep track of the subsets is reduced by taking advantage of their spatial coherence which is captured by the aid of a shortest path quadtree. In particular, experiments on a number of large road networks as well as a theoretical analysis have shown that the storage has been reduced from O(N3) to O(N1.5) (i.e., by an order of magnitude equal to the square root). The precomputation of the shortest paths along the network essentially decouples the process of computing shortest paths along the network from that of finding the neighbors, and thereby also decouples the domain S of the query objects and that of the objects from which the neighbors are drawn from the domain V of the vertices of the spatial network. This means that as long as the spatial network is unchanged, the algorithm and underlying representation of the shortest paths in the spatial network can be used with different sets of objects.