Community mining method and device based on symbol network model

A symbolic network and community mining technology, applied in the network field, can solve the problems of detection accuracy dependence and low accuracy of community mining, and achieve the effect of improving accuracy

Inactive Publication Date: 2016-12-07
SHENZHEN INSTITUTE OF INFORMATION TECHNOLOGY
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AI Technical Summary

Problems solved by technology

However, the above-mentioned symbolic network community discovery algorithms are all optimization algorithms or heuristic algorithms, and their detection accuracy depends on the quality of the designed optimization objective function or heuristic strategy, without considering the generation mechanism of the symbolic network community structure, the accuracy of community mining degree is not high

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  • Community mining method and device based on symbol network model
  • Community mining method and device based on symbol network model
  • Community mining method and device based on symbol network model

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Embodiment Construction

[0022] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0023] In the embodiment of the present invention, the symbolic network model SNM corresponding to the community number K is constructed K , the SNM K =(n, K, Z, π, θ), and the symbolic network model SNM K Fitting with the read symbolic network N, calculating the symbolic network model SNM K The cost function value H of K , to learn the community structure of the symbolic network N; then compare all symbolic network models SNM K The cost function value H of K , select the cost function value H K The smallest symbolic network model SNM K As the optimal model SNM optim , to determine the numb...

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Abstract

The invention is suitable for the field of network technologies and provides a community mining method and device based on a symbol network model. The method comprises steps of reading an adjacent matrix A of a symbol network N, setting the variation range of a community number K as [Kmin, Kmax], and initializing the community number K=Kmin, wherein the node total of the symbol network N is n, and Kmin and Kmax are integers within the range of n; aiming at each community number K, initializing a corresponding symbol network model SNMK, fitting the symbol network model SNMK with the symbol network N, and calculating a cost function value HK of the symbol network model SNMK; comparing all the cost function values HK of the symbol network models SNMK, and selecting a symbol network model SNMK of the minimal cost function value HK as the optimal model SNMoptim; and determining a community to which each node i belongs in the symbol network N according to the optimal model SNMoptim, wherein 0<i<=n. The invention achieves community mining of the symbol network, and effectively improves the accuracy of community mining of the symbol network.

Description

technical field [0001] The invention belongs to the field of network technology, in particular to a community mining method and device based on a symbolic network model. Background technique [0002] Compared with the unsigned network, which can only indicate whether there is a relationship between individuals, the symbolic network can expand the single existence relationship into positive and negative relationships. For example, positive links in social networks indicate friendship, liking, and trust, and negative links indicate hostility, dislike, and distrust; positive links in political networks indicate political alliances, and negative links indicate political hostility. These added symbolic information contribute to a deeper understanding of the hidden laws behind the network. As a kind of important structural pattern ubiquitous in complex networks, community is of great significance for understanding the function and development and evolution of networks / systems. ...

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Application Information

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IPC IPC(8): G06Q50/00
CPCG06Q50/01
Inventor 赵学华陈慧灵杨博刘学艳
Owner SHENZHEN INSTITUTE OF INFORMATION TECHNOLOGY
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