Node-activity-based asymmetrical cell group expansion overlapping cell discovering and predicting method in complex network

A technology of node activity and overlapping communities, applied in complex mathematical operations, instruments, data processing applications, etc., can solve the high error rate of overlapping node allocation, lack of method system for evolution analysis of overlapping communities, and hinder the development of overlapping community theory and applications And other issues

Active Publication Date: 2017-10-10
TONGJI UNIV
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AI Technical Summary

Problems solved by technology

[0013] Existing research is mainly based on methods such as expansion, density, hierarchical clustering, and statistical inference to realize overlapping community discovery, which makes the detection accuracy of overlapping community detection and analysis methods low, the error rate of overlapping node assignment is high,...

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  • Node-activity-based asymmetrical cell group expansion overlapping cell discovering and predicting method in complex network
  • Node-activity-based asymmetrical cell group expansion overlapping cell discovering and predicting method in complex network
  • Node-activity-based asymmetrical cell group expansion overlapping cell discovering and predicting method in complex network

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Experimental program
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Embodiment approach 1

[0032] The steps are described in detail below.

[0033] In the step 1, the definition and analysis of node activity

[0034] In order to measure the activity degree of the node, the present invention expands the node fitness model to obtain the node vitality (Node Vitality). The fitness model is used to measure the competitiveness of different nodes in the evolution network, thereby explaining the multi-scale nature of the dynamic evolution process of the complex network, that is, in addition to high nodes having a greater probability of establishing connections, "high-quality" nodes are also It is easy to create new connections with other nodes, so it has strong competitiveness. However, the original node fitness is a fixed value, and the competitiveness of the node should change. The present invention defines node activity as a real value v associated with node i i ∈[-1,1], v i It describes the inherent ability of node i to quickly create or delete connections during network...

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Abstract

The invention aims to the research on the discovery of overlapping cell in the evolution of a complex network, which does not consider the dynamic evolution, the uneven activity distribution and the multi-scaling of individuals so that the overlapping cell could not improve the NMI (Normalized Mutual Information) and the F-score. Therefore, the method discloses a node-activity-based asymmetrical cell group expansion overlapping cell discovering and predicting method, comprising: first, defining the activity of the nodes; using the activity of the nodes on the objective function for overlapping cell expansion; then, expanding the cell and using the biggest cell group as the expanding seed; and finally, working out the asymmetrical cell group expansion algorithm based on the node activity. According to the invention, it is possible to radically increase the detection accuracy for the overlapping cell in a complex network and to possess a better predicting capability for an overlapping community in the future.

Description

Technical field [0001] The invention relates to the field of complex networks, in particular to a method for discovering and predicting overlapping communities based on asymmetric community expansion based on node activity in complex networks. Background technique [0002] In 2005, Palla et al. proposed the definition of allowing nodes to belong to multiple communities at the same time, that is, allowing communities to overlap. They promoted traditional community discovery problems to overlapping community discovery. In order to obtain overlapping communities, Palla et al. proposed the CPM algorithm (CPM, CliquePercolation Method) based on the nature that the nodes in the community are connected to most other nodes in the community without connecting to all nodes. In the CPM algorithm, first search for a structure called k-clique (a complete subgraph containing at least k nodes and not a subset of any other complete subgraph), and then search for adjacent k-clique (shared k-cliq...

Claims

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Application Information

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IPC IPC(8): G06Q50/00G06F17/10
CPCG06F17/10G06Q50/01
Inventor 程久军吴潇黄震华张长柱秦鹏宇陈向荣杨阳廖竞学邵剑雨尚铮米浩
Owner TONGJI UNIV
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