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An Activity-Performer Bipartite Matrix Generation Algorithm for Analyzing Workflow-supported Human-Resource Affiliations

워크플로우 기반 인적 자원 소속성 분석을 위한 업무-수행자 이분 행렬 생성 알고리즘

  • Ahn, Hyun (Department of Computer Science, Kyonggi University) ;
  • Kim, Kwanghoon (Department of Computer Science, Kyonggi University)
  • Received : 2013.01.23
  • Accepted : 2013.03.21
  • Published : 2013.04.30

Abstract

In this paper, we propose an activity-performer bipartite matrix generation algorithm for analyzing workflow-supported human-resource affiliations in a workflow model. The workflow-supported human-resource means that all performers of the organization managed by a workflow management system have to be affiliated with a certain set of activities in enacting the corresponding workflow model. We define an activity-performer affiliation network model that is a special type of social networks representing affiliation relationships between a group of performers and a group of activities in workflow models. The algorithm proposed in this paper generates a bipartite matrix from the activity-performer affiliation network model(APANM). Eventually, the generated activity-performer bipartite matrix can be used to analyze social network properties such as, centrality, density, and correlation, and to enable the organization to obtain the workflow-supported human-resource affiliations knowledge.

본 논문에서는 워크플로우 기반 인적 자원의 소속성 분석을 위한 업무-수행자 이분 행렬 생성 알고리즘을 제안한다. 워크플로우 기반 인적 자원은 워크플로우 관리 시스템에 의해 관리되는 조직의 모든 수행자들을 말하며, 워크플로우 모델의 실행 과정에서 특정 업무 집합에 참여하게 된다. 이러한 워크플로우 모델에 정의된 수행자들과 업무들과의 소속성을 나타내는 소셜 네트워크를 업무-수행자 소속성 네트워크라 정의하였으며, 본 논문에서 제안하는 알고리즘은 워크플로우 모델로부터 발견된 업무-수행자 소속성 네트워크 모델(APANM)에 대한 이분 행렬을 생성하기 위한 알고리즘이다. 결론적으로, 알고리즘에 의해 생성된 업무-수행자 이분 행렬은 중심성(centrality), 밀집도(density), 상관 관계(correlation)와 같은 다양한 소셜 네트워크 관련 속성들을 분석하는데 적용될 수 있으며, 이를 통해 워크플로우 기반 인적 자원의 소속성에 대한 유용한 지식을 획득할 수 있다.

Keywords

References

  1. C.A. Ellis, G.J. Nutt, "Office Information Systems and Computer Science", ACM Computing Surveys, Vol. 12, No. 1, pp. 27-60, 1980. https://doi.org/10.1145/356802.356805
  2. C.A. Ellis, "Information Control Nets: A Mathmatical Model of Office Information Flow", Proceedings of the Conference on Simulation, Measurement and Modeling of Computer Systems, pp. 225-240, 1979.
  3. D. Knoke, S. Yang, SOCIAL NETWORK ANALYSIS - 2nd Edition, Series: Quantitative Applications in the Social Sciences, SAGE Publications, 2008.
  4. S.P. Borgatti, D.S. Halgin, "Analyzing Affiliation Networks", The Sage Handbook of Social Network Analysis, pp. 417-433, 2010.
  5. K. Faust, "Centrality in Affiliation Networks", Journal of Social Networks, Vol. 19, No. 2, pp. 157-191, 1997. https://doi.org/10.1016/S0378-8733(96)00300-0
  6. D. Grigori, et al., "Business Process Intelligence", Journal of Computer in Industry, Vol. 53, No. 3, pp. 321-343, 2004. https://doi.org/10.1016/j.compind.2003.10.007
  7. K. Kim, C.A. Ellis, "ICN-Based Workflow Model and Its Advances", Handbook of Research on Business Process Modelling, pp. 34-54, 2009.
  8. W.M.P. van der Aalst, et al., "Workflow Mining: a Survey of Issues and Approaches", Journal of Data and Knowledge Engineering, Vol. 47, No. 2, pp. 237-267, 2003. https://doi.org/10.1016/S0169-023X(03)00066-1
  9. W.M.P. van der Aalst, et al., "Discovering Social Networks from Event Logs", Journal of Computer Supported Cooperative Work, Vol. 14, No. 6, pp. 549-593, 2005. https://doi.org/10.1007/s10606-005-9005-9
  10. M. Park, K. Kim, "Control-Path Oriented Workflow Intelligence Analyses", Journal of Information Science and Engineering, Vol. 24, No. 2, pp. 343-359, 2008.
  11. M. Park, K. Kim, "A Workflow Event Logging Mechanism and Its Implications on Quality of Workflows", Journal of Information Science and Engineering, Vol. 26, No. 5, pp. 1817-1830, 2010.
  12. K. Kim, C.A. Ellis, "Workflow Reduction for Reachable-path Rediscovery in Workflow Mining", Foundation and Novel Approaches in Data Mining, Vol. 9, pp. 288-309, 2006.
  13. K. Kim, "A Workflow-based Social Network Discovery and Analysis System", Proceedings of the 1st International Symposium on Data-driven Process Discovery and Analysis, pp. 163-176, 2011.
  14. H. Kim, H. Ahn, K. Kim, "A Workflow Affiliation Network Discovery Algorithm", ICIC Express Letters, Vol. 6, No. 3, pp. 765-770, 2012.
  15. M. Skerlavj, et al., "Patterns and Structures of Intra-organizational Learning Networks within a Knowledge Intensive Organization", Journal of Information Technology, Vol. 25, No. 2, pp. 189-204, 2010. https://doi.org/10.1057/jit.2010.3
  16. S. Huh, "Overview of Business Intelligence Concept", Communications of Korean Institute of Information Scientists and Engineers, Vol. 21, No. 10, pp. 5-11, 2003.
  17. K. Kim, "A Workflow-based Affiliation Network Knowledge Discovery Algorithm", Journal of Korean Society for Internet Information, Vol. 13, No. 2, pp. 109-118, 2012. https://doi.org/10.7472/jksii.2012.13.2.109