Graph partitioning method based on shortest path and density clustering
A density clustering, shortest path technology, applied in special data processing applications, instruments, electrical digital data processing, etc., to achieve good versatility and good segmentation effect.
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[0037] A weighted undirected graph G=(V,E), V={v i}, E={e i}, i={1,2,3,...,n}, w(e i ) means side e i weight; the adjacency list is used as the storage structure of the graph, and the adjacency list information of each node is L(v i )={{v i1 ,e i1},{v i2 ,e i2},{v i3 ,e i3},...,{v im ,e im}}.
[0038] Set the density threshold minPt, the distance threshold minEp, set the initial category k=1, and mark the category of each node as 0, that is, type i =0, i={1,2,3,...,n}.
[0039] Randomly select a node v in V whose category is marked as 0 j , calculate N(v j ). Read the adjacency list information, calculate each node in the adjacency list to v j The path length Dis (that is, connect the node in the adjacency list with v j The weight of the edge), compare the size of Dis and the distance threshold minEp, and add the nodes corresponding to the distance smaller than minEp in the adjacency list to N(v j ), and further in-depth search calculations, that is, reading ...
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