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A Survey of Parallel Community Detection Algorithms

A Survey of Parallel Community Detection Algorithms

Sobin C. C., Vaskar Raychoudhury, Snehanshu Saha
Copyright: © 2017 |Pages: 26
ISBN13: 9781522524984|ISBN10: 1522524983|EISBN13: 9781522524991
DOI: 10.4018/978-1-5225-2498-4.ch001
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MLA

Sobin C. C., et al. "A Survey of Parallel Community Detection Algorithms." Handbook of Research on Applied Cybernetics and Systems Science, edited by Snehanshu Saha, et al., IGI Global, 2017, pp. 1-26. https://doi.org/10.4018/978-1-5225-2498-4.ch001

APA

Sobin C. C., Raychoudhury, V., & Saha, S. (2017). A Survey of Parallel Community Detection Algorithms. In S. Saha, A. Mandal, A. Narasimhamurthy, S. V, & S. Sangam (Eds.), Handbook of Research on Applied Cybernetics and Systems Science (pp. 1-26). IGI Global. https://doi.org/10.4018/978-1-5225-2498-4.ch001

Chicago

Sobin C. C., Vaskar Raychoudhury, and Snehanshu Saha. "A Survey of Parallel Community Detection Algorithms." In Handbook of Research on Applied Cybernetics and Systems Science, edited by Snehanshu Saha, et al., 1-26. Hershey, PA: IGI Global, 2017. https://doi.org/10.4018/978-1-5225-2498-4.ch001

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Abstract

The amount of data generated by online social networks such as Facebook, Twitter, etc., has recently experienced an enormous growth. Extracting useful information such as community structure, from such large networks is very important in many applications. Community is a collection of nodes, having dense internal connections and sparse external connections. Community detection algorithms aim to group nodes into different communities by extracting similarities and social relations between nodes. Although, many community detection algorithms in literature, they are not scalable enough to handle large volumes of data generated by many of the today's big data applications. So, researchers are focusing on developing parallel community detection algorithms, which can handle networks consisting of millions of edges and vertices. In this article, we present a comprehensive survey of parallel community detection algorithms, which is the first ever survey in this domain, although, multiple papers exist in literature related to sequential community detection algorithms.

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