Prediction network unknown connection edge method based on second-order local association information
A technology for forecasting networks and communities, applied in forecasting, instrumentation, data processing applications, etc., can solve problems such as low accuracy and low information utilization, and achieve high accuracy and improve accuracy.
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[0023] The present invention will be further described below in conjunction with the accompanying drawings.
[0024] refer to figure 1 , a method for predicting unknown connections in a network based on second-order local community information, including the following steps:
[0025] Step 1: Establish a network model G(V,E) under the condition that the entire network remains connected, where V is a node in the network, and E is an edge in the network;
[0026] Step 2: Select a pair of nodes i and j without edges in the network as two seed nodes, namely figure 1 In the middle black circle, extract all the first-order common neighbor nodes and second-order common neighbor nodes of i and j and the edges between these nodes, such as figure 1 The white dots and their connected edges constitute a second-order local community, where a node in the middle of a path of length 2 between i and j is a first-order common neighbor, and two nodes in the middle of a path of length 3 are two ...
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