A Graph Embedding-Based Method for Quantifying Structural Differences in Networks
A network structural and quantitative method technology, applied in the field of network structural difference quantification based on graph embedding, can solve problems such as incompleteness, underestimation, and limited information, and achieve accurate quantification
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[0026] The technical solutions of the present invention will be further described below with reference to the accompanying drawings.
[0027] A network structural difference quantification method based on graph embedding, the specific steps are:
[0028] Step (1). Construct the representation vector of the network node;
[0029] The graph embedding method node2vec based on random walk is used to construct the representation vector of network nodes. The complete algorithm of node2vec is as follows:
[0030]
[0031] First, a corresponding network G is constructed according to the input nodes and the edges between the nodes, G=(V, E, W). Among them, V represents a set of network nodes, E represents a set of network edges, and W represents a weight set of network edges. It is assumed that network G has N nodes, and N=100. Since node2vec is a graph embedding method with biased random walk that combines breadth-first search and depth-first search, the corresponding transition ...
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