Multi-resolution community discovering method based on fuzzy clustering

Abstract

The invention provides a multi-resolution community discovering method based on fuzzy clustering. According to local interaction information of adjacent nodes, the structural similarity is introduced for measuring the fuzzy relation between the nodes, fuzzy transitivity of the fuzzy similarity between the nodes in a network topology is partially considered, fuzzy parameters are used for performing set cutting on a fuzzy transitivity matrix to obtain community structures under different resolutions, and therefore network communities can be discovered. Matrix transformation operation is adopted, a network community detection model based on fuzzy clustering is built, iterative optimization processes in a traditional method are reduced, the time complexity is lowered, a large number of experiments prove that the community structures in a network can be effectively revealed, the universality is strong, and the high application value is achieved; network structural analysis and community structural visualization can be effectively achieved.

Description

technical field [0001] The invention relates to the research field of complex network analysis technology, in particular to a multi-resolution community discovery method based on fuzzy clustering. Background technique [0002] As a broad interdisciplinary subject, complex network involves computer, physics, mathematics, information science, system science, network science and other disciplines. It has gradually become a powerful tool to solve complex problems and has a wide range of applications in many fields, such as Social network analysis, bioengineering, economics and finance, electricity and transportation, human behavior analysis, big data analysis, etc. The research and analysis of complex networks has greatly expanded the breadth and depth of people's understanding of the world, and has great practical significance. In a large number of complex network studies, the study of complex network community structure is a major research focus. Generally speaking, for a gi...

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Problems solved by technology

However, a large number of existing community structure detection methods regard this similarity relationship as a deterministic or rigid measure, and such division will lead to unreasonable division of communities. In fact, in real network structures such as social networks, the relationship between entities The similarity relationship is fuzzy or uncertain, and dividing by a certain measure will ignore other important information in the network

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