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논문 기본 정보

자료유형
학술저널
저자정보
(Saveetha University) (Dr. Ambedkar Institute of Technology) (Sri Sivasubramaniya Nadar College of Engineering) (K.Ramakrishnan College of Technology)
저널정보
대한전자공학회 IEIE Transactions on Smart Processing & Computing IEIE Transactions on Smart Processing & Computing Vol.14 No.1
발행연도
수록면
1 - 10 (10page)
DOI
10.5573/IEIESPC.2025.14.1.1

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초록· 키워드

In social and real-time network applications, community detection is the very popular and rapidly expanding field of study. Recently, many community detection approaches have been developed. In instance, community detection has proved to be effective and successful in local development strategies. Nevertheless, there are few basic problems to expose the overlapping communities. Although certain techniques are not sensitive enough to demonstrate widespread overlaps, the maximal approaches allow the seeds to be initialized and parameters to be created. A new unsupervised Map Reduce dependent local expanding technique to overlap community dependent seed node finding is presented in this study. The proposed method finds the leader or seed nodes of communities by using simple graph metrics, including closeness, centrality, degree, and betweenness. It then finds the communities that follow the leader nodes. Map-Reduce-oriented is proposed to utilize the Fuzzy C-Means Clustering approach to find which communities overlap depending on the leader nodes. The experimental outcomes illustrate the proposed method (LBCD), which assess network graph allowed the overlapping community structures, is more effectual and confident when used to entire 11 actual-world data sets.
#Leader nodes #Community detection social network #Big data #Map reduce
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목차

  1. Abstract
  2. 1. Introduction
  3. 2. Related Work
  4. 3. Proposed Architecture
  5. 4. Find the Every Shortest Pair Utilizing Giraph
  6. 5. Degree of Influence (DI) Computation Utilizing Map-reduce Method
  7. 6. Leader Nodes Identification
  8. 7. Community creation
  9. 8. Results with Discussions
  10. 9. Conclusion with future work
  11. References

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