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A fuzzy community mining method for complex networks based on membership degree propagation

A technology of community mining and membership degree, which is applied in the field of complex network fuzzy community mining based on membership degree propagation, can solve problems such as the absence of a unified method, and achieve the effects of ensuring quality, overcoming topology information loss, and quickly selecting

Active Publication Date: 2018-01-19
BEIHANG UNIV
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  • Claims
  • Application Information

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Problems solved by technology

However, currently there is no widely accepted unified method for quality evaluation of fuzzy community mining.

Method used

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  • A fuzzy community mining method for complex networks based on membership degree propagation
  • A fuzzy community mining method for complex networks based on membership degree propagation
  • A fuzzy community mining method for complex networks based on membership degree propagation

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Embodiment Construction

[0032] The present invention will be described in detail below in conjunction with the accompanying drawings.

[0033] refer to figure 1 The overall design diagram of the present invention, the present invention first determines the selection order of the seed nodes according to the basic feature that the degree of the community seed node is usually larger and often greater than the degree of its neighbor nodes: test whether the nodes are in the order of degree from large to small is the seed node, and for nodes with the same degree, the sum of the degrees of its neighbor nodes is considered, that is, the test is carried out in the order of the sum of the degrees of the neighbor nodes from small to large. Therefore, all nodes in the network are sorted as V = {v i}, the sorting satisfies:

[0034] deg(v i )≥deg(v i+1 ) and deg 2 (v i )≤deg 2 (v i+1 )

[0035] deg 2 (v i ) for node v i The sum of the neighbor node degrees of , namely:

[0036]

[0037] where N{v ...

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Abstract

The invention relates to a method for discovering a complex network fuzzy association based on membership transmission. The method comprises the following steps: firstly building a selection framework of association seed nodes and determining a test sequence for selecting the seed nodes by taking the basic characteristics of the association seed nodes as a reference; then building a membership transmission model among network nodes according to the objective laws of various complex networks in the real world, and transmitting the association membership of the seed nodes to non-seed nodes by the model; on this basis, determining a selection rule of the association seed nodes by taking modularity for optimizing an association dividing result as a target; and finally, further optimizing the modularity by adjusting the node association attributes and combining associations after the association seed nodes are selected, and correcting the association membership of each node to obtain the final fuzzy association discovering result. The method has the advantages of stability, robustness and effectiveness; meanwhile, the method also has the flexibility of balancing computation cost and overall performance.

Description

technical field [0001] The invention relates to complex networks, community detection and fuzzy clustering, in particular to mining fuzzy communities in complex networks, in particular to a complex network fuzzy community mining method based on membership degree propagation. Background technique [0002] The aggregation phenomenon of nodes is an important characteristic of complex network topology. In the past ten years, the analysis of community structure in the network has become one of the frontier research hotspots in the field of complex network science. It is found that complex networks in the real world can often be divided into several communities. Within the same community, nodes are closely connected, while nodes belonging to different communities are sparsely connected. Discovering communities in the network can reveal the macro-topological structure of the network, which can play an important supporting role in various applications in different fields. The curr...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30
CPCG06F16/958G06Q50/01
Inventor 陈小武张恒源赵沁平李甲周彬
Owner BEIHANG UNIV