Method of predicting unknown connecting sides of network based on second-order local community and seed node structure information

A seed node and predictive network technology, applied in the direction of data exchange network, digital transmission system, electrical components, etc., can solve the problems of low information utilization rate and low accuracy rate, and achieve improved accuracy, high precision, and good prediction effect Effect

Active Publication Date: 2017-01-18
ZHEJIANG UNIV OF TECH
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Problems solved by technology

[0004] In order to overcome the problems of low accuracy and low information utilization of existing link prediction algorithms, the present inventio...

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  • Method of predicting unknown connecting sides of network based on second-order local community and seed node structure information
  • Method of predicting unknown connecting sides of network based on second-order local community and seed node structure information
  • Method of predicting unknown connecting sides of network based on second-order local community and seed node structure information

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Embodiment Construction

[0024] The present invention will be further described below in conjunction with the accompanying drawings.

[0025] refer to figure 1 , a method for predicting unknown network edges based on second-order local communities and seed node structure information, including the following steps:

[0026] 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;

[0027] Step 2: Select a pair of nodes i and j without edges in the network as two seed nodes, namely figure 1 The black dots in the middle, the number of neighbor nodes of nodes i and j are respectively recorded as k i and k j , extract all the first-order common neighbor nodes and second-order common neighbor nodes of nodes i and j and the edges between these nodes, such as figure 1 The white dots in and their edges form a second-order local community, where the node in the middle of a path of length 2 betwe...

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Abstract

A method of predicting unknown connecting sides of a network based on a second-order local community and seed node structure information comprises the following steps: building a network model, randomly taking a pair of unconnected nodes as seed nodes, recording the number of neighbor nodes of the seed nodes, and acquiring first-order and second-order common neighbor nodes of the seed nodes, wherein the nodes and the connecting sides thereof constitute a second-order local community; recording the total number of nodes and connecting sides of the community; calculating the degree coefficient, side clustering coefficient, simple harmonic average distance and second-order local community coefficient of the community; calculating the similarity score index of the node pair; and traversing the whole network, and for any two unconnected nodes, calculating the similarity score index of the corresponding node pair, sorting the similarity scores of all unconnected node pairs in descending order, and taking node pairs corresponding to the first m indexes as predicted connecting sides. The method considers a second-order local community and seed node structure information, makes full use of the local structure information of a network, has a good prediction effect, and is of high accuracy.

Description

technical field [0001] The invention relates to the field of network and link prediction, in particular to a method for predicting network unknown connection edges based on second-order local communities and seed node structure information. Background technique [0002] With the rapid development of science, human beings have entered the network age. Various technologies and industries based on the Internet have emerged as the times require, greatly improving people's learning and life. We live in all kinds of networks. When you interact with people, you will have a network of relationships, and when you travel, you will have a transportation network. With the rapid development of natural science, we know more and more about the world. The network of human research is becoming larger and more complex. In the context of today's big data, as the size of individual data and the total size of data that need to be processed increase, the average quality of data is declining, w...

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Application Information

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IPC IPC(8): H04L12/24
CPCH04L41/12H04L41/142H04L41/145H04L41/147
Inventor 杨旭华程之肖杰
Owner ZHEJIANG UNIV OF TECH
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