Cited By
View all- Ahn HPham DKim K(2019)An Experimental Analytics on Discovering Work Transference Networks from Workflow Enactment Event LogsApplied Sciences10.3390/app91123689:11(2368)Online publication date: 10-Jun-2019
Discovering work transference networks on workflows
Pages 568 - 572
Abstract
The purpose of this paper1 is to define a conceptual model of organizational worker's transference networks and to devise an formal algorithm for discovering it embedded on a workflow procedure. It is worked out from the strong belief that those work transference networks hidden in workflow enactment activities are able to not only connote the degrees of work-sharing and work-relevancy among workers, but also denote the degree of work-intensity of workers in a workflow-supported organization. In deploying the formal discovery algorithm, we use the information control net theory as a formal representation basis, which is able to graphically and mathemathically represent workflow procedures. Finally, we describe the implications of the discovered work transference network and its analysis results in a workflow-supported organization.
References
[1]
Clarence Ellis, Aubrey Rembert, Jacques Wainer, and Kwanghoon Pio Kim. 2012. Investigations on stochastic information control nets. Information Sciences 194 (2012), 120--137. https://doi.org/
[2]
Haksung Kim, Hyun Ahn, Hyeonil Jeong, and Kwanghoon Pio Kim. 2014. A Workflow Performer-Role Affiliation Networking Knowledge Discovery Algorithm. ICIC Express Letters 8, 3 (2014), 717--722.
[3]
Haksung Kim, Hyun Ahn, and Kwanghoon Pio Kim. 2014. Modeling, Discovering, and Visualizing Workflow Performer-Role Affiliation Networking Knowledge. KSII Transactions on Internet and Information Systems 8, 2 (2014), 689--706. https://doi.org/
[4]
Kwanghoon Kim. 1999. Actor-oriented Workflow Model. In Proceedings of the 2nd international symposium on Cooperative Database Systems for Advanced Applications. 150--164.
[5]
Kwanghoon Kim and Clarence A. Ellis. 2009. Handbook of Research on Business Process Modeling (1st. ed.). IGI Global, Chapter 7. ICN-based workflow model and its advances, 142--171.
[6]
Min-Joon Kim, Hyun Ahn, and Minjae Park. 2015. A GraphML-based Visualization Framework for Workflow-Performers Closeness Centrality Measurements. KSII Transactions on Internet and Information Systems 9, 8 (2015), 3216--3230.
[7]
Min-Joon Kim, Hyun Ahn, and Minjae Park. 2015. A Theoretical Framework for Closeness Centralization Measurements in a Workflow-Supported Organization. KSII Transactions on Internet and Information Systems 9, 9 (2015), 3611--3634.
[8]
Tingyu Liu, Yalong Cheng, and Zhonghua Ni. 2012. Mining Event Logs to Support Workflow Resource Allocation. Knowledge-Based Systems 35 (November 2012), 320--331.
[9]
Minjae Park, Hyun Ahn, and Kwanghoon Pio Kim. 2016. Workflow-supported social networks: Discovery, analyses, and system. Journal of Network and Computer Applications 75 (2016), 355--373.
[10]
Wil M. P. van der Aalst, Hajo A. Reijers, and Minseok Song. 2005. Discovering Social Networks from Event Logs. Computer Supported Cooperative Work 14, 6 (2005), 549--593.
Index Terms
- Discovering work transference networks on workflows
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Published In
December 2017
609 pages
ISBN:9781450352994
DOI:10.1145/3151759
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 04 December 2017
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- Short-paper
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- Ministry of Science, ICT & Future Planning
Conference
iiWAS2017
iiWAS2017: The 19th International Conference on Information Integration and Web-based Applications & Services
December 4 - 6, 2017
Salzburg, Austria
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View all- Ahn HPham DKim K(2019)An Experimental Analytics on Discovering Work Transference Networks from Workflow Enactment Event LogsApplied Sciences10.3390/app91123689:11(2368)Online publication date: 10-Jun-2019
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