Post on 18-Jan-2016
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Workflow Mining: Current Status and Workflow Mining: Current Status and Future DirectionsFuture Directions
Ana Karla A. de Medeiros,
W.M.P van der Aalst and A.J.M.M. Weijters
Eindhoven University of Technology
Department of Information and Technology
a.k.medeiros@tm.tue.nl
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Outline
• Motivation
• Workflow Mining: -algorithm
• Workflow Mining: limitations
• Extensions to Mining Algorithms
• Discussion and Future work
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Workflow Mining – Motivation
– Workflow Mining (What is the process?)
– Delta analysis (Are we doing what was specified?)
– Performance analysis (How can we improve?)
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Workflow Mining – Process log
ABCDABCD
ACBDACBD
EFEF
case 1 : task A case 1 : task A case 2 : task A case 2 : task A case 3 : task A case 3 : task A case 3 : task B case 3 : task B case 1 : task B case 1 : task B case 1 : task C case 1 : task C case 2 : task C case 2 : task C case 4 : task A case 4 : task A case 2 : task B case 2 : task B case 2 : task D case 2 : task D case 5 : task E case 5 : task E case 4 : task C case 4 : task C case 1 : task D case 1 : task D case 3 : task C case 3 : task C case 3 : task D case 3 : task D case 4 : task B case 4 : task B case 5 : task F case 5 : task F case 4 : task D case 4 : task D
• Minimal information in noise-free log: case id’s and task id’s
• Additional information: event type, time, resources, and data
• In this log there are three possible sequences:
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Workflow Mining – Ordering Relations >,,||,#
• Direct succession: x>y iff for some case x is directly followed by y.
• Causality: xy iff x>y and not y>x.
• Parallel: x||y iff x>y and y>x
• Unrelated: x#y iff not x>y and not y>x.
case 1 : task A case 1 : task A case 2 : task A case 2 : task A case 3 : task A case 3 : task A case 3 : task B case 3 : task B case 1 : task B case 1 : task B case 1 : task C case 1 : task C case 2 : task C case 2 : task C case 4 : task A case 4 : task A case 2 : task B case 2 : task B ......
A>BA>BA>CA>CB>CB>CB>DB>DC>BC>BC>DC>DE>FE>F
AABB
AACC
BBDD
CCDD
EEFF
B||CB||CC||BC||B
ABCDABCD
ACBDACBD
EFEF
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Workflow Mining – -algorithm
Let W be a workflow log over T. (W) is defined as follows.
1. TW = { t T W t },
2. TI = { t T W t = first() },
3. TO = { t T W t = last() },
4. XW = { (A,B) A TW B TW a Ab B a W b a1,a2 A a1#W
a2 b1,b2 B b1#W b2 },
5. YW = { (A,B) X (A,B) XA A B B (A,B) = (A,B) },
6. PW = { p(A,B) (A,B) YW } {iW,oW},
7. FW = { (a,p(A,B)) (A,B) YW a A } { (p(A,B),b) (A,B) YW b
B } { (iW,t) t TI} { (t,oW) t TO}, and
8. (W) = (PW,TW,FW).
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Workflow Mining – -algorithm
A
B
C
D
E F
ABCDABCD
ACBDACBD
EFEF
AABB
AACC
BBDD
CCDD
EEFF
B||CB||CC||BC||B
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Workflow Mining – -algorithm
• If log is complete with respect to relation >, it can be used to mine SWF-net without short loops
• Structured Workflow Nets (SWF-nets) have no implicit places and the following two constructs cannot be used:
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• Problematic constructs– Short loops – Invisible Tasks– Synchronization of OR-join places– Duplicate Tasks– Implicit Places – Non-free Choice
Workflow Mining – -algorithm limitations
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• Problematic constructs– Short loops – Invisible Tasks– Synchronization of OR-join places– Duplicate Tasks– Implicit Places – Non-free Choice
Workflow Mining – -algorithm limitations
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-algorithm limitations – Short Loops
One-length
Two-length
B>B and not B>B implies BB (impossible!)
A>B and B>A implies A||B and B||A instead of AB and BA
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• Problematic constructs– Short loops – Invisible Tasks– Synchronization of OR-join places – Duplicate Tasks – Implicit Places– Non-free Choice
Workflow Mining – -algorithm limitations
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-algorithm limitations – Invisible Tasks
Nets are behaviorally equivalent!
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• Problematic constructs– Short loops – Invisible Tasks– Synchronization of OR-join places – Duplicate Tasks – Implicit Places– Non-free Choice
Workflow Mining – -algorithm limitations
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-algorithm limitations – Synchronization of OR-join places
But...
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• Problematic constructs– Short loops – Invisible Tasks– Synchronization of OR-join places – Duplicate Tasks– Implicit Places – Non-free Choice
Workflow Mining – -algorithm limitations
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-algorithm limitations – Duplicate Tasks
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• Problematic constructs– Short loops – Invisible Tasks– Synchronization of OR-join places – Duplicate Tasks– Implicit Places – Non-free Choice
Workflow Mining – -algorithm limitations
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-algorithm limitations – Implicit Places
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• Problematic constructs– Short loops – Invisible Tasks– Synchronization of OR-join places – Duplicate Tasks– Implicit Places – Non-free Choice
Workflow Mining – -algorithm limitations
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-algorithm limitations – Non-free Choice
But...
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• Some problematic constructs relate because– Can have same complete workflow log and/or– Same set of ordering relations
Workflow Mining – Trade-offs between Problematic Constructs
XYXY
XAAYXAAY
XXAA
A A YY
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• Process mining = 3-phase process1. Pre-processing
2. Processing
3. Post-processing
• Example for 1-lenght loops in SWF-nets
Workflow Mining – Extensions to Mining Algorithms
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Workflow Mining – Extensions to Mining Algorithms (Example)
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-algorithm cannot mine correctly – Short loops– Invisible tasks– Duplicate Tasks– Implicit Places– Non-free Choice– Synchronization of OR-join Places
• Extensions are possible, but relations between problematic constructs imply in trade-offs
Workflow Mining – Discussion and Future Work
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• Future steps– Extend the class of WF-nets -algorithm can correctly
mine– Create mining algorithms to handle workflows beyond
WF-nets– Develop mining heuristics to deal with noisy or
incomplete workflow logs
Workflow Mining – Discussion and Future Work
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Questions?