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Process discovery Sander Leemans.

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Presentation on theme: "Process discovery Sander Leemans."— Presentation transcript:

1 Process discovery Sander Leemans

2 Process discovery rediscoverability Soundness
execution process discovery fitness precision generalisation system event log process model rediscoverability Soundness Fitness event log – model Precision model – event log Generalisation model – “future” Rediscoverability model – system (language-equivalence) Sander Leemans

3 Goal Sound Rediscovers Fast Balances fitness/precision/generalisation
Sander Leemans

4 Existing algorithms  Sound Rediscovered Fast  Balanced  Sound
 Slow  Balanced α ILP Evolutionary Tree Miner Heuristics Miner  Sound  Rediscovered  Slow  Balanced  Sound  Rediscovered  Fast  Balanced Sander Leemans

5 Incomplete information
Outline Infrequency Incomplete information rediscoverability Sander Leemans

6 Process trees τ τ a b c d e τ τ a b e c d Sander Leemans

7 Incomplete information
Outline Infrequency Incomplete information rediscoverability Sander Leemans

8 Inductive Miner Split log Recurse Select cut
A,B,C A,C,B Split log Recurse Select cut (operator & activity partition) B,C C,B A A B C B C Sander Leemans

9 IM: cut selection Partition directly-follows graph
B Partition directly-follows graph : edges crossing one-way only : all edges crossing in both ways A,B,C A,C,B A C A,C,DC,A,D C,D,A B,C,DC,B,D C,D,B A B C D Sander Leemans

10 IM: rediscoverability
= Process tree No duplicate activities No “short loops” Directly-follows (graph) complete Noise-free Sander Leemans

11 Hall of Algorithms  Sound  Rediscovered  Fast  Balanced
(guarantees fitness) Inductive Miner Evolutionary Tree Miner  Sound  Rediscovered  Slow  Balanced Sander Leemans

12 Question: rediscoverability
Is there an optimum? Inductive Miner α Petri net synthesis Directly-follows complete Noise-free Directly-follows complete Noise-free 2-follows complete Behaviour complete Noise-free low high high low Process tree No duplicate activities No short loops Process tree Not too much duplicate activities - Sander Leemans

13 Incomplete information
Outline Infrequency Incomplete information rediscoverability Sander Leemans

14 Challenges Infrequent behaviour Incomplete information Sander Leemans

15 Infrequency A B C A,B,C A,C,B ... (x1000) B,A,C A B C A B C
Sander Leemans

16 Handling infrequency 1 B B A A 1000 Activity-wise comparison: C C
B → A infrequent A B C A,B,C A,C,B ... (x1000) B,A,C A B C Sander Leemans

17 Hall of Algorithms (2)  Sound  Rediscovered  Fast  Balanced
Inductive Miner Inductive Miner - infrequent Evolutionary Tree Miner  Sound  Rediscovered  Slow  Balanced Sander Leemans

18 Incomplete information
Outline Infrequency Incomplete information rediscoverability Sander Leemans

19 Incompleteness : all edges crossing in both ways
A,C,D C,A,D C,D,A B,C,D C,B,D C,D,B A B C D A B C D A B C D Inductive Miner: overestimate α miner: garbage Sander Leemans

20 Handling incompleteness
A B 0.1 A C 1 A D 1 B C 1 B D 0.3 C D 0.3 A B 0.8 A C 0 A D 0 ….. A B C D A B C D Average 0.6 Average 0.825 A B C D Estimate pairwise probabilities Find cut with highest average estimate Sander Leemans

21 Hall of Algorithms (3)  Sound  Rediscovered  Fast  Balanced
Inductive Miner Inductive Miner - infrequent Evolutionary Tree Miner Inductive Miner - incompleteness  Sound  Rediscovered  Slow  Balanced  Sound  Rediscovered  Slow ? Balanced  Less information

22 Incomplete information
Outline Infrequency Incomplete information rediscoverability Sander Leemans

23 Validation 12 real-life event logs 2 hours max + soundness
fitness precision generalisation system event log process model 12 real-life event logs 2 hours max + soundness + simplicity + completed or not + mining time Sander Leemans

24 Basic: IM Sander Leemans

25 Infrequency: IMi Sander Leemans

26 Comparison: ETM Sander Leemans

27 Comparison Thanks to the structure, there is room for trade-off.
Sander Leemans

28 Can we look through the event log?
Question: validation Can we look through the event log? fitness precision generalisation system event log process model ? Generalisation using test sets / k-fold cross validation? Sander Leemans

29 Conclusion Goal: sound, rediscover, fast, balances
Q1: improve rediscoverability Q2: validation to system Sander Leemans

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