Computer Science ›› 2018, Vol. 45 ›› Issue (2): 171-174.doi: 10.11896/j.issn.1002-137X.2018.02.030

Previous Articles     Next Articles

Dynamic Community Detection Based on Evolutionary Spectral Method

FU Li-dong and NIE Jing-jing   

  • Online:2018-02-15 Published:2018-11-13

Abstract: In order to effectively analyze the function and characteristics of the community structure in the dynamic network,the module density function and the negative average correlation function were optimized based on the evolutionaryclustering algorithm under the evolutionary time smoothing framework,and the theoretical feasibility was demonstrated.The evolution spectrum algorithm was proposed based on community structure of the dynamic network.The accuracy and effectiveness of the proposed algorithm was verified and compared with other algorithms in the computer synthesis and real dynamic network respectively.The experimental results show that the proposed algorithm is still very accurate and effective in the community detection of dynamic network.

Key words: Dynamic network,Community structure,Module density,Negative average correlation,Evolution spectrum

[1] NOWACKA-WOSZUK J,PRUSZYNSKA-OSZMALEK E,SZ-YDLOWSKI M.Nutrition modulates Fto and Irx3 gene transcript levels,but does not alter their DNA methylation profiles in rat white adipose tissues[J].Gene,2017,610:44-48.
[2] REN L K,LI H J,JIA C L,et al.Near Linear Time Community Detection Algorithm Based on Dynamical Evolution [J].Computer Science,2016,3(6A):395-399,412.(in Chinese) 任泺锟,李慧嘉,贾传亮,等.近似线性时间的社团结构动态演化挖掘算法[J].计算机科学,2016,43(6A):395-399,412.
[3] CRAENE B D,BERX G.Regulatory networks defining EMTduring cancer initiation and progression[J].Nature Review Cancer,2013,3(2):97-110.
[4] LI H J.Fast Algorithm for Detecting Muti-scale DverlappingCommunity Structure Based on Information Spreading[J].Computer Science,2014,41(9):125-131.(in Chinese) 李慧嘉.基于信息扩散的多尺度重叠社团快速探测算法[J].计算机科学,2014,1(9):125-131.
[5] YU S Y,WANG H M.Scientific collaboration:a social network analysis based on literature of animal-derived regenerative implantable medical devices[J].Regenerative Biomaterials,2016,3(3):197-203.
[6] LI Z P,ZHANG S H,WANG R S,et al.Quantitative function for community detection.https://www.ncbi.nlm.nih,gov/pubmed/18517463 .
[7] GUPTA M,GAO J,AGGARWAL C,et al.Outlier detection for temporal data:a survey[J].IEEE Transaction on Knowledge and Data Engineering,2014,6(9):2250-2267.
[8] EGIZI A,FEFFERMAN N H,FONSECA D M.Evidence that implicit assumptions of ‘no evolution’ of disease vectors in changing environments can be violated on a rapid imescale.http://resb.royalsocietypublishing.org/content/royptb/370/1665/20140136.full.pdf .
[9] MA X K,DONG D.Evolutionary nonegative matrix factoriza-tion algorithms for community detection in dynamic networks[J].IEEE Transactions on Knowledge and Data Engineering,2017,29(5):1045-1058.
[10] FOLINO F,PIZZUTI C.An evolutionary multi-objective disco-very in dynamic networks[J].IEEE Transactions on Knowledge and Data Engineering,2014,26(8):1838-1852.
[11] QIN X,LIANG W,YUAN C A,et al.Image Segmentation Algorithm of Spectral Clustering Optimized by Genetic[J].Computer Science,2017,44(1):100-102.(in Chinese) 覃晓,梁伟,元昌安,等.基于遗传优化谱聚类的图形分割方法 [J].计算机科学,2017,4(1):100-102.
[12] CHI Y,SONG X D,ZHOU D Y,et al.On evolutionary spectral clustering[J].ACM Transactions on Knowledge Discovery from Data,2009,3(4):1-30.
[13] FOLINO F,PIZZUTI C.An evolutionary multi-objective ap-proach for community discovery in dynamic networks[J].IEEE Transactions on Knowledge and Data Engineering,2014,26(8):1838-1852.
[14] WANG P Z,GAO L,MA X K.Dynamic community detection based on network structural perturbation and Topological similarity[J].Journal of Statistical Mechanics:Theory and Experiment,2017,1(1):013401.

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!