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Process discovery: Inductive Miner

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Presentation on theme: "Process discovery: Inductive Miner"— Presentation transcript:

1 Process discovery: Inductive Miner
Sander Leemans D. Fahland W.M.P van der Aalst

2 Process discovery system log process model S.J.J. Leemans

3 Quality = Sound Simple fast Fitting Precise System behaviour
Complete log Recorded log fast Fitting Precise = Log Discover model S.J.J. Leemans

4 Results with incomplete logs
not fitting not sound not simple not sound Flower model not precise α ILP Heuristics Miner Evolutionary Tree Miner not fitting not sound not fast

5 Outline {<a,b,c>, <a,c,b>, <a,d,e>,
System behaviour {<a,b,c>, <a,c,b>, <a,d,e>, <a,d,e,f,d,e>} = S.J.J. Leemans

6 Block-structured Petri nets
τ a b c d e τ x /\ Activities Sequence Loop Parallel Exclusive choice Sound a b c d e Sander Leemans

7 Outline System behaviour = S.J.J. Leemans

8 Divide & conquer a {<a,b,c>, <a,c,b>, <a,d,e>,
<a,d,e,f,d,e>} {<a>, <a>, <a>} {<b,c>, <c,b>, <d,e>, <d,e,f,d,e>} recurse recurse S.J.J. Leemans

9 Finding operator {<b,c>, <c,b>, <d,e>,
<d,e,f,d,e>} recurse a b c d e f a {<a,b,c>, <a,c,b>, <a,d,e>, <a,d,e,f,d,e>} Find cut in directly-follows graph Sequence: edges crossing one-way only S.J.J. Leemans

10 recurse … {d,e,f} {b,c} { , } { <b,c> <c,b> , <d,e>
a x {<b,c>, <c,b>, <d,e>, <d,e,f,d,e>} { , } { <b,c> <c,b> , d e b c f {<b,c>, <c,b>} {<d,e>, <d,e,f,d,e>} <d,e> <d,e,f,d,e> { , } } Exclusive choice: no crossing edges S.J.J. Leemans

11 … one more recursion … {f} {d,e} {< < >, >} {< d,e
x a {< < >, >} {< d,e >, {<b,c>, <c,b>} {<d,e>, <d,e,f,d,e>} < d,e , f , {< >} d,e >} {<d,e>} {<f>} f e d d e f Loop: identify body and loopback parts (assumption: start/end activities disjoint) S.J.J. Leemans

12 … last recursion {b} {c} {< < > >} {< < b , c >,
x f a e d {b} {c} {< < > >} {< < b , c >, >} {< < > >} {<b,c>, <c,b>} c b {<b>} b {<c>} c b c Parallel: all possible crossing edges S.J.J. Leemans

13 Result τ a b c d e f x f a e d b c S.J.J. Leemans

14 No cut y z x a x x y z b c S.J.J. Leemans

15 ? Inductive Miner ? Divide activities Select operator Split log
Else: flower model Split log Recurse on splitted logs {c,d} {a,b} ? {c} {d} Sander Leemans

16 Outline System behaviour = S.J.J. Leemans

17 Rediscoverability Complete log System behaviour
= (language equivalent) = (normal form) Log Discover model Block-structured with Start\end activities of loop disjoint No duplicate activities No silent activities (τ) x Directly-follows graph complete Noise-free S.J.J. Leemans

18 Incomplete logs Sound Simple polynomial Fitting Most precise
System behaviour Complete log Sound Simple Incomplete log polynomial Fitting Most precise (by framework; bring your own operator) S.J.J. Leemans

19 Future Work Generalise Block-structured
Start\end activities of loop must be disjoint No duplicate activities No silent activities (τ) Directly-follows graph complete Noise-free x S.J.J. Leemans

20 You have been watching Sound Simple polynomial Fitting Most precise
System behaviour Complete log Sound Simple Incomplete log polynomial Fitting Most precise (by framework; bring your own operator) S.J.J. Leemans


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