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http://dx.doi.org/10.7472/jksii.2015.16.3.71

Performance Analysis of an Estimated Closeness Centrality Ranking Algorithm in Large-Scale Workflow-supported Social Networks  

Kim, Jawon (Dept. of Computer Engineering, Sungkyul University)
Ahn, Hyun (Dept. of Computer Science, Kyonggi University)
Kim, Kwanghoon (Dept. of Computer Science, Kyonggi University)
Publication Information
Journal of Internet Computing and Services / v.16, no.3, 2015 , pp. 71-77 More about this Journal
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.
Keywords
Workflow-supported Social Network; Estimated Closeness Centrality; Ranking Algorithm;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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