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Jia W, Ma X. Clustering of multi-layer networks with structural relations and conservation of features. Appl Soft Comput 2023. [DOI: 10.1016/j.asoc.2023.110272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023]
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He C, Zheng Y, Cheng J, Tang Y, Chen G, Liu H. Semi-supervised overlapping community detection in attributed graph with graph convolutional autoencoder. Inf Sci (N Y) 2022. [DOI: 10.1016/j.ins.2022.07.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
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Xu XL, Xiao YY, Yang XH, Wang L, Zhou YB. Attributed network community detection based on network embedding and parameter-free clustering. APPL INTELL 2022. [DOI: 10.1007/s10489-021-02779-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
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Dynamic Community Discovery Method Based on Phylogenetic Planted Partition in Temporal Networks. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12083795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
As most of the community discovery methods are researched by static thought, some community discovery algorithms cannot represent the whole dynamic network change process efficiently. This paper proposes a novel dynamic community discovery method (Phylogenetic Planted Partition Model, PPPM) for phylogenetic evolution. Firstly, the time dimension is introduced into the typical migration partition model, and all states are treated as variables, and the observation equation is constructed. Secondly, this paper takes the observation equation of the whole dynamic social network as the constraint between variables and the error function. Then, the quadratic form of the error function is minimized. Thirdly, the Levenberg–Marquardt (L–M) method is used to calculate the gradient of the error function, and the iteration is carried out. Finally, simulation experiments are carried out under the experimental environment of artificial networks and real networks. The experimental results show that: compared with FaceNet, SBM + MLE, CLBM, and PisCES, the proposed PPPM model improves accuracy by 5% and 3%, respectively. It is proven that the proposed PPPM method is robust, reasonable, and effective. This method can also be applied to the general social networking community discovery field.
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Lu DD, Qi J, Yan J, Zhang ZY. Community detection combining topology and attribute information. Knowl Inf Syst 2022. [DOI: 10.1007/s10115-021-01646-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
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Embedding regularized nonnegative matrix factorization for structural reduction in multi-layer networks. Appl Soft Comput 2021. [DOI: 10.1016/j.asoc.2021.107781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
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A survey about community detection over On-line Social and Heterogeneous Information Networks. Knowl Based Syst 2021. [DOI: 10.1016/j.knosys.2021.107112] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
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Ma C, Lin Q, Lin Y, Ma X. Identification of multi-layer networks community by fusing nonnegative matrix factorization and topological structural information. Knowl Based Syst 2021. [DOI: 10.1016/j.knosys.2020.106666] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
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Co-regularized nonnegative matrix factorization for evolving community detection in dynamic networks. Inf Sci (N Y) 2020. [DOI: 10.1016/j.ins.2020.04.031] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
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Lin Q, Lin Y, Yu Q, Ma X. Clustering of Cancer Attributed Networks via Integration of Graph Embedding and Matrix Factorization. IEEE ACCESS 2020. [DOI: 10.1109/access.2020.3034623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
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