A type-2 fuzzy community detection model in large-scale social networks considering two-layer graphs

被引:12
作者
Naderipour, Mansoureh [1 ]
Zarandi, Mohammad Hossein Fazel [1 ]
Bastani, Susan [2 ]
机构
[1] Amirkabir Univ Technol, Dept Ind Engn, Polytech Tehran, POB 15875-4413, Tehran, Iran
[2] Alzahra Univ, Dept Social Sci & Econ, Tehran 1993893973, Iran
关键词
Community detection; Overlapping communities; Structural/attribute similarities; Two-layer graph; Type-2 fuzzy clustering; LOGIC APPLICATIONS; SETS; CLASSIFICATION;
D O I
10.1016/j.engappai.2019.07.021
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper mainly aims to identify communities with different interactions between nodes in complex networks. Community detection algorithms partition vertices into densely-connected components in a complex network. In recent researches, a node is related to multiple aspects of relationships resulting in new challenges in social networks. The two aspects of relationships could be shown as a two-layer graph which comprises two graphs dependent on each other; and each graph shows a specific aspect of the interaction. In this research, a new community detection model is proposed based on the possibilistic c-means clustering model considering two-layer graphs (PCMTL) in order to detect overlapping communities based on the two-layer graphs using both structural and attribute similarities in large-scale social networks. The nodes are assigned to communities by upper and lower membership values that are indicative of the degree of belonging to the communities through type-2 fuzzy membership values, and the suggested values of interval type-2 fuzzy membership determine how a node belongs to a community with regard to two different aspects of interactions in a two-layer graph. Moreover, according to the proposed model, a validity index is introduced to assess the suggested model in comparison to the approach existing in the literature. Ultimately, two artificial and two real large-scale social networks are used to validate the performance of the suggested model.
引用
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页数:21
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