• Journal of Internet Computing and Services
    ISSN 2287 - 1136(Online) / ISSN 1598 - 0170 (Print)
    http://jics.or.kr/

An Estimated Closeness Centrality Ranking Algorithm for Large-Scale Workflow Affiliation Networks


Do-kyong Lee, Hyun Ahn, Kwang-hoon Pio Kim, Journal of Internet Computing and Services, Vol. 17, No. 1, pp. 47-54, Feb. 2016
10.7472/jksii.2016.17.1.47, Full Text:
Keywords: Affiliation Network, Estimated Closeness Centrality, Ranking Algorithm

Abstract

A type of workflow affiliation network is one of the specialized social network types, which represents the associative relation between actors and activities. There are many methods on a workflow affiliation network measuring centralities such as degree centrality, closeness centrality, betweenness centrality, eigenvector centrality. In particular, we are interested in the closeness centrality measurements on a workflow affiliation network discovered from enterprise workflow models, and we know that the time complexity problem is raised according to increasing the size of the workflow affiliation network. This paper proposes an estimated ranking algorithm and analyzes the accuracy and average computation time of the proposed algorithm. As a result, we show that the accuracy improves 47.5%, 29.44% in the sizes of network and the rates of samples, respectively. Also the estimated ranking algorithm's average computation time improves more than 82.40%, comparison with the original algorithm, when the network size is 2400, sampling rate is 30%.


Statistics
Show / Hide Statistics

Statistics (Cumulative Counts from November 1st, 2017)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article
[APA Style]
Do-kyong Lee, Hyun Ahn, & Kwang-hoon Pio Kim (2016). An Estimated Closeness Centrality Ranking Algorithm for Large-Scale Workflow Affiliation Networks. Journal of Internet Computing and Services, 17(1), 47-54. DOI: 10.7472/jksii.2016.17.1.47.

[IEEE Style]
D. Lee, H. Ahn and K. P. Kim, "An Estimated Closeness Centrality Ranking Algorithm for Large-Scale Workflow Affiliation Networks," Journal of Internet Computing and Services, vol. 17, no. 1, pp. 47-54, 2016. DOI: 10.7472/jksii.2016.17.1.47.

[ACM Style]
Do-kyong Lee, Hyun Ahn, and Kwang-hoon Pio Kim. 2016. An Estimated Closeness Centrality Ranking Algorithm for Large-Scale Workflow Affiliation Networks. Journal of Internet Computing and Services, 17, 1, (2016), 47-54. DOI: 10.7472/jksii.2016.17.1.47.