Abstract
Social networks play an important role in everyday life. Nowadays there is various research that concentrates on detecting communities within these networks. Traditionally most of the community detection algorithms focus on detecting disjoint networks. However there is a need for overlapping community detection. In recent years there have been some attempts at detecting overlapping communities. Most of these techniques concentrate on just detecting these communities, none of this research tries to detect the maximal set of these communities which gives more stability. In this paper we propose a new method called Maximal-DSHRINK that allows us to detect the maximal set of overlapping communities within a social network. We show that the maximal set provides us with better quality in terms of modularity gain.
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Wei, E.H.C., Koh, Y.S., Dobbie, G. (2013). Finding Maximal Overlapping Communities. In: Bellatreche, L., Mohania, M.K. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2013. Lecture Notes in Computer Science, vol 8057. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40131-2_27
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DOI: https://doi.org/10.1007/978-3-642-40131-2_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40130-5
Online ISBN: 978-3-642-40131-2
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