DocumentCode
2428398
Title
Research on finding community structure based on filtration network model
Author
Shen, Yi ; Pei, Wenjiang ; Li, Tao ; Liu, Jiming ; Yang, Lei ; Wang, Shaoping ; He, Zhenya
Author_Institution
Dept. of Radio Eng., Southeast Univ., Nanjing
fYear
2008
fDate
7-11 June 2008
Firstpage
20
Lastpage
23
Abstract
By defining community recursive coefficient M, we propose a new efficient algorithm called filtration split algorithm for discovering community structure in complex networks. By optimizing the M of child-networks based on dynamic recursive principle, the local communities are discovered automatically. Theoretical analysis and experiment results show that the algorithm can filtrate more than one edge once and make the networks split in parallel. For a network with n vertices, m edges, and c communities, the computation complexity is less than O((c+1)m+(c+1)). For many real-world networks are sparse m~n and c+1 Ltn, our algorithm can run in essentially linear time O((c+1)n).
Keywords
computational complexity; parallel algorithms; child-network; community recursive coefficient; community structure; complex network; computation complexity; dynamic recursive principle; filtration network model; filtration split algorithm; linear time; parallel network; Complex networks; Computer networks; Distribution functions; Filtration; Helium; Joining processes; Neural networks; Signal processing; Signal processing algorithms; Symmetric matrices; Community Recursive Coefficient; Community Structure; Dynamic Recursive Principle; Filtration Split Algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks and Signal Processing, 2008 International Conference on
Conference_Location
Nanjing
Print_ISBN
978-1-4244-2310-1
Electronic_ISBN
978-1-4244-2311-8
Type
conf
DOI
10.1109/ICNNSP.2008.4590301
Filename
4590301
Link To Document