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dc.contributor.authorSarswat A.-
dc.contributor.authorRam Mohana Reddy, Guddeti-
dc.date.accessioned2020-03-31T14:15:22Z-
dc.date.available2020-03-31T14:15:22Z-
dc.date.issued2019-
dc.identifier.citationAdvances in Intelligent Systems and Computing, 2019, Vol.707, pp.491-500en_US
dc.identifier.uri10.1007/978-981-10-8639-7_51-
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/13788-
dc.description.abstractOverlapping community detection in social networks is known to be a challenging and complex NP-hard problem. A large number of heuristic approaches based on optimization functions like modularity and modularity density are available for community detection. However, these approaches do not always give an optimum solution, and none of these approaches are able to clearly provide a stable overlapping community structure. Hence, in this paper, we propose a novel hybrid algorithm to detect the overlapping communities based on the community forest model and Nash equilibrium. In this work, overlapping community has been detected using backbone degree and expansion of the community forest model, and then a Nash equilibrium is found to get a stable state of overlapping community arrangement. We tested the proposed hybrid algorithm on standard datasets like Zachary’s karate club, football, etc. Our experimental results demonstrate that the proposed approach outperforms the current state-of-the-art methods in terms of quality, stability, and less computation time. © Springer Nature Singapore Pte Ltd. 2019en_US
dc.titleA novel hybrid algorithm for overlapping community detection in social network using community forest model and nash equilibriumen_US
dc.typeBook Chapteren_US
Appears in Collections:3. Book Chapters

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