Method for querying road network k aggregation nearest neighboring node based on Voronoi graph
A nearest neighbor, query method technology, applied in the field of spatial database, can solve problems such as poor performance
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[0051] Figure 4 is a hypothetical NVD where p 1 , p 2 ,…, p 14 is the target node, q 1 , q 2 , q 3 is the query point. Note that the path between vertices in NVC and the path between vertices between NVCs are not drawn in the figure, but the road network distance from the query point to some target nodes is marked with a dotted line. In addition, the common edges between NVCs are not stored in the computer. We draw them in order to see the adjacent relationship between NVCs clearly. In fact, the adjacent relationship between NVCs is in the form of a table stored.
[0052] Now calculate the 2-ANN:
[0053] 1. First find out the 1-NN of the query point through the R tree index, and initialize the priority queue H = {( p 1 , 4), ( p 2 , 4), ( p 3 , 4)}, S 1 = { p 1}, S 2 = { p 2}, S 3 = { p 3};
[0054] 2. Then calculate q 1 The next NN( p 2 ), q 3 The next NN( p 2 ), q 2 The next NN( p 1 ), then update the priority queue H = {( ...
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