An Efficient Hierarchy Algorithm for Community Detection in Complex Networks. (23rd October 2014)
- Record Type:
- Journal Article
- Title:
- An Efficient Hierarchy Algorithm for Community Detection in Complex Networks. (23rd October 2014)
- Main Title:
- An Efficient Hierarchy Algorithm for Community Detection in Complex Networks
- Authors:
- Zhang, Lili
Ye, Qing
Shao, Yehong
Li, Chenming
Gao, Hongmin - Other Names:
- Kuo Ren-Jieh Academic Editor.
- Abstract:
- Abstract : Community structure is one of the most fundamental and important topology characteristics of complex networks. The research on community structure has wide applications and is very important for analyzing the topology structure, understanding the functions, finding the hidden properties, and forecasting the time-varying of the networks. This paper analyzes some related algorithms and proposes a new algorithm—CN agglomerative algorithm based on graph theory and the local connectedness of network to find communities in network. We show this algorithm is distributed and polynomial; meanwhile the simulations show it is accurate and fine-grained. Furthermore, we modify this algorithm to get one modified CN algorithm and apply it to dynamic complex networks, and the simulations also verify that the modified CN algorithm has high accuracy too.
- Is Part Of:
- Mathematical problems in engineering. Volume 2014(2014)
- Journal:
- Mathematical problems in engineering
- Issue:
- Volume 2014(2014)
- Issue Display:
- Volume 2014, Issue 2014 (2014)
- Year:
- 2014
- Volume:
- 2014
- Issue:
- 2014
- Issue Sort Value:
- 2014-2014-2014-0000
- Page Start:
- Page End:
- Publication Date:
- 2014-10-23
- Subjects:
- Engineering mathematics -- Periodicals
510.2462 - Journal URLs:
- https://www.hindawi.com/journals/mpe/ ↗
http://www.gbhap-us.com/journals/238/238-top.htm ↗ - DOI:
- 10.1155/2014/874217 ↗
- Languages:
- English
- ISSNs:
- 1024-123X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 25893.xml