Towards comprehensive support for organizational mining

1. Towards comprehensive support for organizational mining Presenter : Yu-hui Huang Authors : Minseok Song , Wil M.P. van der Aalst 國立雲林科技大學 National Yunlin University of Science and Technology DSS 2008

2. Outline • Motivation • Objective • Methodology • Experiment • Conclusion

3. Motivation • Today event logs are widely available and growing . • we can constructing a process flow by analyze the even log and improve it.

4. Objective • The primary goal of process mining is to extract knowledge from these logs and use it for a detailed analysis of reality • To discover organizational models and social networks from the process log.

5. Methodology • Process mining：it is to extract information from event logs.

6. Methodology • Process model： • Organization model：

7. Methodology • Process log：

8. Methodology • Organizational model markup language：

9. Methodology • Organizational mining： (1)organizational model mining • Task-base: similar skills and knowledge to perform the tasks • Default mining： • Metrics based： • Agglomerative Hierarchical Clustering (AHC)： • Case-base: different skills and work together • Metrics based on joint cases： (2)social network analysis (3)information flows

10. Methodology • Metrics based (task-base)：

11. Methodology • AHC (task-base )：

12. Methodology • Metrics based on joint cases ：

13. Methodology Information flows between organizational entities • Social network analysis：

14. Experiment

15. Experiment

16. Experiment

17. Conclusion • To evaluate the organizational model mining results , conformance test methods should be developed. • We can apply non-disjoint clustering methods to reflect an organization in which originators play multiple roles. 17

18. Comments • Advantage • … • Drawback • …. • Application • …