Heterogeneous social network community detection method based on genetic algorithm

Abstract

The invention discloses a heterogeneous social network community detection method based on a genetic algorithm and the heterogeneous social network community detection method is used for mainly solving the problem that the accuracy rate of the detected community structure is obviously reduced when the social network data and relationship are large in scale in the prior art. The implementation scheme of the method comprises the following steps: constructing an adjacency matrix for describing a heterogeneous social network according to the number of nodes in the network and information of relation among the nodes; generating random symbolic coding individual according to the adjacency matrix; evaluating the advantages and disadvantages of the individuals by taking the improved modularity density as a fitness function; optimizing the individual according to the fitness function value of the individual by adopting a genetic algorithm; reducing the optimized individual with the highest fitness function value into a corresponding heterogeneous network, and decoding to obtain a partitioned community structure. The experimental result proves that the community structure of the heterogeneous social network can be effectively detected, the detection accuracy rate is high, and the method can be used for community detection of a large-scale heterogeneous social network.

Description

technical field [0001] The invention belongs to the technical field of social network computing, in particular to a heterogeneous social network community detection method, which can be used for structural research on complex social systems and large-scale social networks. Background technique [0002] A social system refers to a system composed of social people and the economic, political and cultural relations between social people and social people. For example, families, political parties, and communities are all social systems at different levels. A social system is a typical complex system, which can be abstracted into a complex network, that is, the entities in the system are abstracted into nodes, and the connections between entities are abstracted into edges between nodes, so that a network composed of nodes and edges is obtained. social network. The complex network obtained by the abstraction of social system is called social network. [0003] Community detection...

AI Technical Summary

Problems solved by technology

Although this method can divide the community structure of heterogeneous social networks, due to the large number of social network types, large amounts of data, and complex relationships, there are scalability problems. significantly lower rate

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