Journal of Internet Computing and Services (인터넷정보학회논문지)

Korean Society for Internet Information (한국인터넷정보학회)
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Performance Analysis of an Estimated Closeness Centrality Ranking Algorithm in Large-Scale Workflow-supported Social Networks

대규모 워크플로우 소셜 네트워크의 추정 근접 중심도 랭킹 알고리즘 성능 분석

  • Kim, Jawon (Dept. of Computer Engineering, Sungkyul University) ;
  • Ahn, Hyun (Dept. of Computer Science, Kyonggi University) ;
  • Kim, Kwanghoon (Dept. of Computer Science, Kyonggi University)
  • Received : 2015.02.02
  • Accepted : 2015.03.25
  • Published : 2015.06.30
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Abstract

This paper implements an estimated closeness centrality ranking algorithm in large-scale workflow-supported social networks and performance analyzes of the algorithm. Existing algorithm has a time complexity problem which is increasing performance time by network size. This problem also causes ranking process in large-scale workflow-supported social networks. To solve such problems, this paper conducts comparison analysis on the existing algorithm and estimated results by applying estimated-driven RankCCWSSN(Rank Closeness Centrality Workflow-supported Social Network). The RankCCWSSN algorithm proved its time-efficiency in a procedure about 50% decrease.

본 논문에서는 대규모 워크플로우 기반 소셜 네트워크를 위한 추정 근접 중심도 랭킹 알고리즘을 구현하고, 그에 대한 성능 분석을 수행한다. 기존의 근접 중심도 분석 방법은 특정 노드와 다른 모든 노드들 간의 최단거리를 구하므로 네트워크의 크기가 커짐에 따라 근접 중심도 분석 시간이 기하급수적으로 증가하는 문제점을 가진다. 이로 인해 대규모 소셜 네트워크의 근접 중심도 랭킹 과정에도 계산시간 문제를 가진다. 이러한 문제점을 개선하고자 본 논문에서는 추정기법을 활용한 근접 중심도 랭킹 알고리즘을 구현하며 기존 알고리즘과의 성능 분석을 수행한다. 이는 약 50%의 계산 시간 단축 결과를 보여주었다.

Keywords

References

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  2. An Estimated Closeness Centrality Ranking Algorithm and Its Performance Analysis in Large-Scale Workflow-supported Social Networks vol.10, pp.3, 2016, https://doi.org/10.3837/tiis.2016.03.031