Survey of community discovery method of heterogeneous network
Community structure is an important field in the research of complex networks,and it is also one of the important characteristics of complex networks.It is found that the community structure in the network plays an important role in understanding network functions.Through in-depth research on the li...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | ZH |
| Publicado: |
Hebei University of Science and Technology
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/b43ff9216774485f9282f76e54edbf1b |
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| Sumario: | Community structure is an important field in the research of complex networks,and it is also one of the important characteristics of complex networks.It is found that the community structure in the network plays an important role in understanding network functions.Through in-depth research on the literature of heterogeneous network community discovery at home and abroad,a more comprehensive summary of the existing heterogeneous network community discovery algorithm is carried out.Firstly,by summarizing the literature of heterogeneous network community discovery at home and abroad,the basic overview of heterogeneous network community discovery is given,and the basic definition of related issues in the field of heterogeneous network community discovery is defined.Then,it introduces the heterogeneous network community discovery algorithm and the main evaluation index,and classifies the existing methods by using different network structures and algorithms.Finally,the development trend of heterogeneous network community discovery algorithms is summarized and prospected,and the future research focus can be focused on the following aspects:1) Exploring the evaluation criteria of community discovery based on heterogeneous networks to promote the rapid development of this field Development;2) Design a more general algorithm model to solve the problem of the number of unknown communities caused by prior knowledge;3) Carry out more research on dynamic networks. |
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