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A Scheme to Design Community Detection Algorithms in Various Networks

School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON K1N 6N5, Canada
Author to whom correspondence should be addressed.
Future Internet 2019, 11(2), 41;
Received: 21 December 2018 / Revised: 31 January 2019 / Accepted: 10 February 2019 / Published: 12 February 2019
(This article belongs to the Special Issue 10th Anniversary Feature Papers)
PDF [423 KB, uploaded 12 February 2019]


Network structures, consisting of nodes and edges, have applications in almost all subjects. A set of nodes is called a community if the nodes have strong interrelations. Industries (including cell phone carriers and online social media companies) need community structures to allocate network resources and provide proper and accurate services. However, most detection algorithms are derived independently, which is arduous and even unnecessary. Although recent research shows that a general detection method that serves all purposes does not exist, we believe that there is some general procedure of deriving detection algorithms. In this paper, we represent such a general scheme. We mainly focus on two types of networks: transmission networks and similarity networks. We reduce them to a unified graph model, based on which we propose a method to define and detect community structures. Finally, we also give a demonstration to show how our design scheme works. View Full-Text
Keywords: social network; network modelling; community detection; network clustering social network; network modelling; community detection; network clustering

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Lu, H.; Nayak, A. A Scheme to Design Community Detection Algorithms in Various Networks. Future Internet 2019, 11, 41.

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