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Abductive Workflow Mining Using Binary Resolution on Task Successor Rules. Scott Buffett National Research Council Canada University of New Brunswick RuleML 2008 Orlando, Florida, October 30, 2008. B. A. C. E. D. Workflow Mining. Transaction log containing a number of events
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Abductive Workflow Mining Using Binary Resolution on Task Successor Rules Scott Buffett National Research Council Canada University of New Brunswick RuleML 2008 Orlando, Florida, October 30, 2008
B A C E D 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
B A C E D Using Workflow to Measure Compliance • Compare observed activity with accepted model • ACDE? • If discrepancies exist, behavior may be non-compliant
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
D E A C F B 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 Task B: Access credit report
D E A C F B Abductive Workflow Mining • Reduce the problem to mining workflow that necessarily implies that the critical activity must be executed • We call this “abductive workflow” Presence of task C (process loan application form) implies B
F C C A A C B B F C F D E A C F B Some Example Abductive Workflows for Critical Task “B”
A C C C B C F Desirable Properties • Trace minimality: • Completeness:
Finding Desirable Workflows • Task successor rules • Indicate activity that immediately follows certain tasks • Example workflow traces: • PQR, PRS, RMN, TVQ • Critical activity: R
Divide Positive and Negative Traces Traces: PQR, PRS, RMN, TVQ, Critical: R • Positive traces: PQR, PRS, RMN • Negative traces: TVQ
Remove Critical Activity Traces: PQR, PRS, RMN, TVQ, Critical: R • Positive traces: PQR, PRS, RMN • Remove critical activity: PQ, PS, MN • Negative traces: TVQ
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’
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 -> N N -> w’ PQ -> w’ PS -> w’ MN -> w’
~PQS ~P~Qw’ ~PSw’ ~Sw’ ~Pw’ 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’
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
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
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