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![Page 1: Abductive Workflow Mining Using Binary Resolution on Task Successor Rules Scott Buffett National Research Council Canada University of New Brunswick RuleML.](https://reader035.fdocuments.us/reader035/viewer/2022081517/5a4d1b0c7f8b9ab05998bf35/html5/thumbnails/1.jpg)
Abductive Workflow Mining Using Binary Resolution on Task Successor Rules
Scott BuffettNational Research Council Canada
University of New Brunswick
RuleML 2008
Orlando, Florida, October 30, 2008
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Workflow Mining
• Transaction log containing a number of events
• Each event is labeled by a task and a case
• Tasks executed a case give a trace
• ABCE, ABDE, ACBE, ADBE
A E
B
C
D
Task CaseA 1A 2A 3C 3B 1B 2A 4B 3D 2C 1E 1B 4D 4E 2E 3E 4
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3
Using Workflow to Measure Compliance
• Compare observed activity with accepted model
• ACDE?
• If discrepancies exist, behavior may be non-compliant
A E
B
C
D
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Problems with Using Workflow
• Detected non-compliant behaviour does not imply inappropriate activity
• Behaviour might be OK, but not captured during workflow mining
• Workflow model not 100% accurate
• Errors in task / case labelings
• Noise
• Process may have evolved or changed
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Solution
• Identify the tasks that are of high importance
• Example process: Bank loan application– A: Enter financial data– B: Access credit report– C: Process loan application form– D: Process pre-approved loan form– E: Approve loan– F: Reject loan application
• Cases observed: ABCE, ABCF, ADE
A
B
D
F
E
C
Task B: Access credit report
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Abductive Workflow Mining
• Reduce the problem to mining workflow that necessarily implies that the critical activity must be executed
• We call this “abductive workflow”
A
B
D
F
E
C
Presence of task C (process loan application
form) implies B
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Some Example Abductive Workflows for Critical Task “B”
F
C F
C
F
A B C
A B
C
A
B
D
F
E
C
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Desirable Properties
• Trace minimality:
• Completeness:
A B CC
C
F
C
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Finding Desirable Workflows
• Task successor rules
• Indicate activity that immediately follows certain tasks
• Example workflow traces:– PQR, PRS, RMN, TVQ
• Critical activity: R
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Divide Positive and Negative Traces
Traces: PQR, PRS, RMN, TVQ, Critical: R
• Positive traces: PQR, PRS, RMN
• Negative traces: TVQ
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Remove Critical Activity
Traces: PQR, PRS, RMN, TVQ, Critical: R
• Positive traces: PQR, PRS, RMN• Remove critical activity: PQ, PS, MN
• Negative traces: TVQ
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Add Dummy Tasks
Traces: PQR, PRS, RMN, TVQ, Critical: R
• Positive traces: PQR, PRS, RMN• Remove critical activity: PQ, PS, MN• Add dummy tasks: PQw’, PSw’, MNw’
• Negative traces: TVQ• Add dummy tasks: TVQw0’
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Task Successor Rules
• One for every subsentence in positive traces (except w’)
• Positive: PQw’, PSw’, MNw’• Negative: TVQw0’
• Rules:P -> Q, S Q -> w’, w0’S -> w’ M -> NN -> w’ PQ -> w’PS -> w’ MN -> w’
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Finding Abductive Workflows
• Convert to CNF~P, Q, S ~Q, w’, w0’~S, w’ ~M, N~N, w’ ~P, ~Q, w’~P, ~S, w’ ~M, ~N, w’
• Binary resolution, generate clauses where w’ is the only positive literal
P -> w’
~PQS
~Sw’~PSw’
~P~Qw’
~Pw’
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Finishing the Example
• Complete set of abductive traces:– P, S, M, N, PS, MN, PQ
• Task-minimal abductive traces:– P, S, M, N
• Complete workflows:– {P,M}, {P,N}, {P,M,N}, {P,S,M}, {P,S,N}, {P,S,M,N}
• Complete, trace-minimal:– {P,M}, {P,N}
PQR, PRS, RMN
TVQ
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Results
• Test size reduction of abductive workflows• Uses a naïve method for finding abductive workflows, complete
but not necessarily minimal• Thus provides a lower bound on size reduction• Mines entire workflow and extracts abductive workflow • Ran on example log files accompanying ProM software
Our Miner Alpha Miner
Statistic (Avg) Orig. Workflow Abd. Workflow Orig. Workflow Abd. Workflow
# of transitions 156.2 37.2 12.0 5.6
# of arcs 318.6 77.0 33.2 15.6
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Conclusions
• Abductive workflows provide a condensed model, adequate for validating particular critical activity
• Mitigate a number of problems inherent in compliance checking
• Rules can help determine such workflows, with desirable properties
• Potential for significant decreases in size of workflow model was demonstrated
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