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Overlapping Community Detection by Node-Weighting

Authors:

Juan LiAuthors Info & Claims

ICCDA '18: Proceedings of the 2nd International Conference on Compute and Data Analysis

Pages 70 - 74

https://doi.org/10.1145/3193077.3193086

Published: 23 March 2018 Publication History

Abstract

Community detection is an important task with great practical value for understanding the structure and function of complex networks. However, in many social networks, a node may belong to more than one community. Thus, the detection of overlapping community is more significant. The local expansion algorithm using seeds to find overlapping communities is becoming increasingly popular, but how to choose suitable seeds and expand the local communities effectively is still a great challenge. In this paper, we propose a new overlapping community detection algorithm based on node-weighting (OCDNW). The main idea of the algorithm is to find a good seed and then greedily expand it based on an improved community quality metric. Finally it optimizes the community structure to ensure the quality of community partitioning. Experimental results on synthetic and real world networks prove that the proposed algorithm can detect overlapping communities successfully and outperform other state-of-the-art methods.

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Cited By

Win EKhine M(2023)Overlapped Community Detection using Extended Node Similarity by Local Expansion2023 IEEE Conference on Computer Applications (ICCA)10.1109/ICCA51723.2023.10181997(266-270)Online publication date: 27-Feb-2023
https://doi.org/10.1109/ICCA51723.2023.10181997
Rashid YBhat J(2023)Topological to deep learning era for identifying influencers in online social networks :a systematic reviewMultimedia Tools and Applications10.1007/s11042-023-16002-883:5(14671-14714)Online publication date: 4-Jul-2023
https://doi.org/10.1007/s11042-023-16002-8

Index Terms

Overlapping Community Detection by Node-Weighting
1. Networks
  1. Network types
    1. Overlay and other logical network structures
      1. Social media networks

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cover image ACM Other conferences

ICCDA '18: Proceedings of the 2nd International Conference on Compute and Data Analysis

March 2018

94 pages

ISBN:9781450363594

DOI:10.1145/3193077

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 March 2018

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ICCDA 2018

ICCDA 2018: 2018 The 2nd International Conference on Compute and Data Analysis

March 23 - 25, 2018

IL, DeKalb, USA

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Cited By

Win EKhine M(2023)Overlapped Community Detection using Extended Node Similarity by Local Expansion2023 IEEE Conference on Computer Applications (ICCA)10.1109/ICCA51723.2023.10181997(266-270)Online publication date: 27-Feb-2023
https://doi.org/10.1109/ICCA51723.2023.10181997
Rashid YBhat J(2023)Topological to deep learning era for identifying influencers in online social networks :a systematic reviewMultimedia Tools and Applications10.1007/s11042-023-16002-883:5(14671-14714)Online publication date: 4-Jul-2023
https://doi.org/10.1007/s11042-023-16002-8

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