discovering processes from event logs

8/15/2019 Discovering Processes From Event Logs

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rocess Mining:Discovering processes from eventlogs

All truths are easy to understand once they are discovered;the point is to discover them.

Galileo Galilei (1564 - 1642)

Prof.dr.ir. Wil van der Aalst Eindhoven University of Technology

Department of Information and Technology P.O. Box 51 ! 5"## $B Eindhoven

The %etherlands&.m.p.v.d.aalst'tm.t(e.nl


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Outline• BPM research in Eindhoven• Process Mining• ProM

– Architecture – Process mining plug-ins

• Alpha-algorithm• Multi-phase mining• Genetic mining

– Anal sis plug-ins – !onformance testing plug-in

– "#" chec$er plug-in – %ocial net&or$ plug-in – !onvertors 'e-mail( %taff&are( )n!oncert( %AP( etc.*

• !onclusion


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BPM research in Eindhoven


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Computer Science/information Systems in Eindhoven

TU/e

TM

(Technology Management)MCS

(Math. and Comp. Science)

IS

(Information Systems)CS

(Computer Science)

BPM

(Business Process Management)

Math.

ICTA

SE

IS

(Information Systems)

BETA


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Research within the BPM group• Wor$flo& management s stems• Process modeling 'design and redesign*

• Process anal sis 'validation( verification( andperformance anal sis*

• Process mining

Often +ased on Petri nets


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Analysis and improvement

of resource-constrainedwor flow processesMariska Netjes

simulationusing final

circumstances

real data

simulationusing initial

circumstances

after WfM implementation

before WfM implementation

,a-measurement

,+-measurement

-measurement

a-measurement

+-measurement

/-measurement


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Product-driven process designIrene Vanderfeesten

handle insurance claim

registration

chec! policy

chec! damage

e"aluate claim

pay damage

re#ect claim

$uery policy data

$uery payments data phone

send fa%

send letter

dial

&'

&' send letter

administrati"e e"aluation

thorough e"aluation

minimal e"aluation

e"aluation y traffic e%pert

e"aluation y department man

e"aluation y fire e%pert

chec! fire damage

chec! other types of damage

minimal damage chec!

chec! car damage

chec! car damage *++,

chec! car damage *++-

ma!e appointment "isual inspection

is)part)of

speciali*es

try again


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!mproving wor distri"utionmechanisms in #$M systemsMaja Pesic


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Patterns in process-aware

information systemsNataliya Mulyar

pattern standard

P/0 1M0 BPE0 0A 2 3S40 BPM0 3SCI

Se$uence , , , , , , ,

Parallel Split , , , , , , ,

Synchroni5ation , , , , , , ,

E%clusi"e Choice , , , , , , ,

Simple Merge , , , , , , ,

Multi Choice , - , - , - -

Synchroni5ing Merge , - , - , - -

Multi Merge - - - - - ,6- ,6-

/iscriminator - - - - - - -

Ar itrary Cycles , - - - - - -

Implicit Termination , - , - , , ,

MI 7ithout Synchroni5ation , , , , , , ,

MI 7ith a Priori /esign Time

'no7ledge, , , , , , ,

MI 7ith a Priori 8untime 'no7ledge - , - - - - -

MI 7ithout a Priori 8untime'no7ledge - - - - - - -

/eferred Choice - , , , - , ,

Interlea"ed Parallel 8outing - - ,6- - - - -

Milestone - - - - - - -

Cancel Acti"ity - , , , , , ,

Cancel Case - , , , , , ,


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%enetic process mining Ana Karla Alves de Medeiros


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Process mining in case handlingsystemsC ristian !"nt er


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Process mining&

a formal approach#oud$ijn van %ongen


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'erification of wor flowprocesses&ric Verbeek


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(A#)& (et Another #or flow )anguage


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• Arthur ter 0ofstede 'patterns( 1AW" def.*• Marlon 2umas 'BABE"( %O!*• "achlan Aldred '1AW" engine( comm. pats*• "indsa Bradford '1AW" designer*

• #ore 34ellheim '1AW" logging( timers*• Gu 5edding '1AW" forms*• 6ic$ 5ussell '&or$ distri+ution7transactions*

• Moe W nn 'verification( optimi8ation*• Michael Adams 'fle9i+ilit *


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Process Mining

processdesign

implementation7configuration

processenactment

diagnosis


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Motivation: 5eversing the process

• Process mining can +e used for:

– Process discover 'What is the process;* – 2elta anal sis 'Are &e doing &hat &as specified;* – Performance anal sis '0o& can &e improve;*

processmining

5egister order

Prepareshipment

%hipgoods

5eceivepa ment

'5e*send+ill

!ontactcustomer

Archiveorder


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Overvie&

*+ "asicperformancemetrics

,+ process modelStartRegister order

Prepareshipment

Ship goods

-Re+send "ill

Receive paymentContactcustomer

Archive order

End

.+ organi ational model 0+ social networ

1+ performancecharacteristics

If …then …

2+ auditing/security

&&&.processmining.org


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"et us focus on mining process models <

*+ "asicperformancemetrics

,+ process modelStart

Registerorder

Prepareshipment

Ship goods

-Re+send "ill

Receive paymentContactcustomer

Archive order

End

.+ organi ational model 0+ social networ

1+ performancecharacteristics

If …then …

2+ auditing/security

... and a ver simple approach: #he alpha algorithm


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Process log

• Minimal information inlog: case id=s and tas$id=s.

• Additional information:event t pe( time(resources( and data.

• )n this log there are threepossi+le se>uences: – AB!2 – A!B2 – E3

case 1 : task A

case 2 : task A

case 3 : task A

case 3 : task B

case 1 : task B

case 1 : task C

case 2 : task C

case 4 : task A

case 2 : task B

case 2 : task D

case 5 : task E

case 4 : task C

case 1 : task D

case 3 : task C

case 3 : task D

case 4 : task B

case 5 : task F

case 4 : task D


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?( →(@@( relations

• 3irect succession : 9?iff for some case 9 isdirectl follo&ed + .

• Causality : 9→ iff 9?and not ?9.

• Parallel : 9@@ iff 9? and?9

• Choice : 9 iff not 9?and not ?9.

case 1 : task A

case 2 : task A

case 3 : task A

case 3 : task B

case 1 : task B

case 1 : task C

case 2 : task C

case 4 : task A

case 2 : task B

case 2 : task D

case 5 : task E

case 4 : task C

case 1 : task D

case 3 : task Ccase 3 : task D

case 4 : task B

case 5 : task F

case 4 : task D

A?B

A?!B?!B?2!?B!?2E?3

A→B A→!B→2! →2E→3

B@@!!@@B


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Basic idea ',*

9

9→


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Basic idea ' *

9→ ( 9→8( and @@8

9

8


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Basic idea '/*

9→ ( 9→8( and 8

9

8


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Basic idea ' *

9→8( →8( and 9@@

9

8


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Basic idea 'C*

9→8( →8( and 9

9

8


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)t is not that simple: Basic alpha algorithm

"et W +e a &or$flo& log over #. α 'W* is defined as follo&s.,. # W D t∈ # | ∃σ ∈ W t ∈ σF(

. # ) D t∈ # | ∃σ ∈ W t D first ' σ* F(

/. # O D t∈ # | ∃σ ∈ W t D last ' σ* F(. W D 'A(B* | A⊆ # W ∧ B ⊆ # W ∧ ∀ a ∈ A∀+ ∈ B a →W + ∧ ∀ a,(a ∈ A a , W a ∧ ∀+,(+ ∈ B + , W + F(

C. 1 W D 'A(B*∈ | ∀ 'A ′(B′*∈ A ⊆ A′ ∧B ⊆ B ′⇒ 'A(B* D 'A ′(B′* F(

H. PW D p'A(B* | 'A(B* ∈ 1 W F∪ iW(oWF(I. 3 W D 'a(p 'A(B** | 'A(B* ∈ 1 W ∧ a ∈ A F ∪ 'p 'A(B*(+* | 'A(B* ∈ 1 W ∧ + ∈ B

F ∪ 'iW(t* | t ∈ # )F ∪ 't(oW* | t ∈ # OF( and

8. α 'W* D 'P W(# W(3 W*.The alpha algorithm has een pro"en to e correct for a large class of free-choice nets.


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E9amplecase 1 : task A

case 2 : task Acase 3 : task Acase 3 : task Bcase 1 : task Bcase 1 : task Ccase 2 : task C

case 4 : task Acase 2 : task Bcase 2 : task Dcase 5 : task Ecase 4 : task Ccase 1 : task D

case 3 : task Ccase 3 : task Dcase 4 : task Bcase 5 : task Fcase 4 : task D

A

B

!

2

E 3

α (3)

3


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!hallenges

• 5efining e9isting algorithm for 'control-flo&7processperspective* – 'idden tasks – %uplicate tasks – Non(free(c oice constructs

– )oops – %etecting concurrency *implicit or e+plicit, – Mining and e+ploiting time – %ealing $it noise – %ealing $it incompleteness

• Mining other perspectives 'data( resources( roles(


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3EM4 Alpha algorithm

9: cases;< performers


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ProM framewor


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ProM Staffware

!nConcert

M5 Series

$orkflo$ management systems

$)4#er

Jectus

%ie+el

case andling - C.M systems

SAP R/.

Baa6

Peoplesoft

&.P systems

common GM" format for storing7e9changing &or$flo& logs

input7outputCore

Plugins

ProM

framework

visuali8ation anal sis

alpha algorithm geneticalgorithm#singhua alpha

algorithmMulti phasealgorithms

social net&or$miner

case datae9traction propert verifier

E6ternal7ools

6etMiner Jiscover 888888

888


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!onverter plug-in: EMailAnal 8er


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M" format


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ProM architecture


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%tep ,: Get instances


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%tep : Pro4ect


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%tep /: Aggregate


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%tep : Map onto EP!


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%tep C: Map onto Petri net 'or other language*


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Mining plug-in: Genetic Miner


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Overvie& of approach


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Anal sis plug-in: %ocial net&or$ miner


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!li>ues


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%6 +ased on hand-over of &or$ metric

density of network is 0.225


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%6 +ased on &or$ing together 'and ego net&or$*


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Anal sis plug-in: "#" chec$er


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Anal sis plug-in: !onformance chec$er

/o they agree=


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%creenshot

(Also runs on Mac.)


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Other anal sis plug-ins


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More demos9


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More information

http&//www8wor flowcourse8com

http&//www8wor flowpatterns8com

http&//www8processmining8org

discovering processes from event logs

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