A Parallel Community Structure Mining Method in Big Social Networks
Joint Authors
Yang, Shuqiang
Jin, Songchang
Yu, Philip S.
Li, Shudong
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-04-27
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Community structure plays a key role in analyzing network features and helping people to dig out valuable hidden information.
However, how to discover the hidden community structures is one of the biggest challenges in social network analysis, especially when the network size swells to a high level.
Infomap is a top-class algorithm in nonoverlapping community structure detection.
However, it is designed for single processor.
When tackling large networks, its limited scalability makes it less effective in fully utilizing server resources.
In this paper, based on infomap, we develop a scalable parallel nonoverlapping community detection method, Pinfomr (parallel Infomap with MapReduce), which utilizes the MapReduce framework to solve the two problems.
Experiments on artificial networks and real datasets show that our parallel method has satisfying performance and scalability.
American Psychological Association (APA)
Jin, Songchang& Yu, Philip S.& Li, Shudong& Yang, Shuqiang. 2015. A Parallel Community Structure Mining Method in Big Social Networks. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1075100
Modern Language Association (MLA)
Jin, Songchang…[et al.]. A Parallel Community Structure Mining Method in Big Social Networks. Mathematical Problems in Engineering No. 2015 (2015), pp.1-13.
https://search.emarefa.net/detail/BIM-1075100
American Medical Association (AMA)
Jin, Songchang& Yu, Philip S.& Li, Shudong& Yang, Shuqiang. A Parallel Community Structure Mining Method in Big Social Networks. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1075100
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1075100