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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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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
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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.

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

Page 2: Abductive Workflow Mining Using Binary Resolution on Task Successor Rules Scott Buffett National Research Council Canada University of New Brunswick RuleML.

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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

Page 3: Abductive Workflow Mining Using Binary Resolution on Task Successor Rules Scott Buffett National Research Council Canada University of New Brunswick RuleML.

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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

Page 4: Abductive Workflow Mining Using Binary Resolution on Task Successor Rules Scott Buffett National Research Council Canada University of New Brunswick RuleML.

4

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

Page 5: Abductive Workflow Mining Using Binary Resolution on Task Successor Rules Scott Buffett National Research Council Canada University of New Brunswick RuleML.

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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

Page 6: Abductive Workflow Mining Using Binary Resolution on Task Successor Rules Scott Buffett National Research Council Canada University of New Brunswick RuleML.

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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

Page 7: Abductive Workflow Mining Using Binary Resolution on Task Successor Rules Scott Buffett National Research Council Canada University of New Brunswick RuleML.

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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

Page 8: Abductive Workflow Mining Using Binary Resolution on Task Successor Rules Scott Buffett National Research Council Canada University of New Brunswick RuleML.

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Desirable Properties

• Trace minimality:

• Completeness:

A B CC

C

F

C

Page 9: Abductive Workflow Mining Using Binary Resolution on Task Successor Rules Scott Buffett National Research Council Canada University of New Brunswick RuleML.

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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

Page 10: Abductive Workflow Mining Using Binary Resolution on Task Successor Rules Scott Buffett National Research Council Canada University of New Brunswick RuleML.

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Divide Positive and Negative Traces

Traces: PQR, PRS, RMN, TVQ, Critical: R

• Positive traces: PQR, PRS, RMN

• Negative traces: TVQ

Page 11: Abductive Workflow Mining Using Binary Resolution on Task Successor Rules Scott Buffett National Research Council Canada University of New Brunswick RuleML.

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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

Page 12: Abductive Workflow Mining Using Binary Resolution on Task Successor Rules Scott Buffett National Research Council Canada University of New Brunswick RuleML.

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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’

Page 13: Abductive Workflow Mining Using Binary Resolution on Task Successor Rules Scott Buffett National Research Council Canada University of New Brunswick RuleML.

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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’

Page 14: Abductive Workflow Mining Using Binary Resolution on Task Successor Rules Scott Buffett National Research Council Canada University of New Brunswick RuleML.

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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’

Page 15: Abductive Workflow Mining Using Binary Resolution on Task Successor Rules Scott Buffett National Research Council Canada University of New Brunswick RuleML.

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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

Page 16: Abductive Workflow Mining Using Binary Resolution on Task Successor Rules Scott Buffett National Research Council Canada University of New Brunswick RuleML.

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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

Page 17: Abductive Workflow Mining Using Binary Resolution on Task Successor Rules Scott Buffett National Research Council Canada University of New Brunswick RuleML.

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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

Page 18: Abductive Workflow Mining Using Binary Resolution on Task Successor Rules Scott Buffett National Research Council Canada University of New Brunswick RuleML.

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