Efficient Comparison of Process Models using Tabu Search Algorithm

MACSPro'2019 - Modeling and Analysis of Complex Systems and Processes, Vienna
21 - 23 March 2019

Andrey Skobtsov, Anna Kalenkova

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Transcript

1. Efficient Comparison of Process Models using Tabu Search Algorithm A.V. Skobtsov, A.A.Kalenkova 23.03.2019
2. Process mining Process ISO 9000:2005 “Set of interrelated or interacting activities which transforms inputs into outputs” Mining
3. Process mining The number of information systems around us is constantly growing… We don't always know how they are actually used:  What actions are most often performed?  In what order?  Are there bottlenecks?  How far we are from the expected behavior of the system.
4. Process mining The number of information systems around us is constantly growing… We don't always know how they are actually used:  What actions are most often performed?  In what order?  Are there bottlenecks?  How far we are from the expected behavior of the system.
5. Process mining User interaction:  Internet marketing;  E-government services;  … Complex multi-component systems (software process mining)
6. Process mining a a a a a a b b b b b b b b c c c c c c c d d d d d d d d d e e e e e e e e a b b a a b c Process-Aware Information Systems Industry a b c d f e Discovery • Discovery
7. Process mining a a a a a a b b b b b b b b c c c c c c c d d d d d d d d d e e e e e e e e a b b a a b c Process-Aware Information Systems Industry a b c d f e Enhancement • Enhancement
8. Process mining a a a a a a b b b b b b b b c c c c c c c d d d d d d d d d e e e e e e e e a b b a a b c Process-Aware Information Systems Industry a b c d f e Discovery Conformance checking Enhancement • Conformance checking
9. Process mining. Conformance checking L2L – Comparison of event structures L2M – Replay techniques M2M - Must be something visual?
10. Finding Minimal Graph Edit Distance register sign in fill the form select payment type pay register sign in fill the form
11. A* Algorithm register sign in fill the form select payment type pay register sign in fill the form cost=0 register sign in fill the form select payment type pay register sign in fill the form cost=0 register sign in fill the form select payment type pay register sign in fill the form cost=10 (Levenshtein distance) … register register
12. register sign in fill the form select payment type pay register sign in fill the form cost=13 (Levenshtein distance) register sign in fill the form select payment type pay register sign in fill the form cost=10 (deletion cost) … register sign in fill the form select payment type pay register sign in fill the form cost=0 A* Algorithm
13. … register sign in fill the form select payment type pay register sign in fill the form cost=10 (Levenshtein Distance) register sign in fill the form select payment type pay register sign in fill the form cost=10 (Deletion cost) … … … … … NP problem A* Algorithm
14. Greedy algorithm ... ... ... ... . . . . . . . . . . . . . . Possible solutions
15. Greedy algorithm ... ... ... ... . . . . . . . . . . . . . . Possible solutions
16. Greedy algorithm ... ... ... ... . . . . . . . . . . . . . . Possible solutions
17. Greedy algorithm ... ... ... ... . . . . . . . . . . . . . . Possible solutions
18. Greedy algorithm ... ... ... ... . . . . . . . . . . . . . . Possible solutions
19. Greedy algorithm ... ... ... ... . . . . . . . . . . . . . . Possible solutions
20. Greedy algorithm ... ... ... ... . . . . . . . . . . . . . . Possible solutions
21. Greedy algorithm ... ... ... ... . . . . . . . . . . . . . . Possible solutions
22. Greedy algorithm ... ... ... ... . . . . . . . . . . . . . . Possible solutions
23. Tabu search algorithm ... ... ... ... . . . . . . . . . . . . . . Possible solutions x Tabu list =<x>
24. Tabu search algorithm ... ... ... ... . . . . . . . . . . . . . . Possible solutions x Tabu list =<x, y> y
25. Tabu search algorithm ... ... ... ... . . . . . . . . . . . . . . Possible solutions x Tabu list =<x, y, z> y z
26. BPMNDiffViz Tool https://pais.hse.ru/research/projects/CompBPMN
27. Experimental results. BPMN models discovered from artificial event logs (different algorithms)
28. Experimental results. BPMN models discovered from real event logs (different algorithms)
29. Experimental results. BPMN models discovered from real event logs (different parts of logs)
30. Future work Industry  New suboptimal methods  New application fields Theory  Compare with other conformance checking methods  Formal languages  Different discovery algorithms (different structure of process models)
31. Thank you!