Process Mining Control flow process discovery Fabrizio Maria Maggi (based on Process Mining book – Springer copyright 2011 and lecture material by Marlon.

Process MiningControl flow process discovery

Fabrizio Maria Maggi

(based on Process Mining book – Springer copyright 2011 and lecture material by Marlon Dumas, Wil van der Aalst and Ana

Karla Alves de Medeiros http://www.processmining.org)

http://www.processmining.org/

Process Mining

Control-Flow Mining

EventEventLogLog

Discovery Techniques: Discovery Techniques: Control-Flow MiningControl-Flow Mining

MinedMinedModelModel

1. Start

2. Get Ready

3. Travel by Train

4. Beta Event Starts

5. Visit Brewery

6. Have Dinner

7. Go Home

8. Travel by Train

1. Start

2. Get Ready

3. Travel by Train


5. Give a Talk

6. Visit Brewery

7. Have Dinner

8. Go Home

9. Travel by Train

1. Start

2. Get Ready

3. Travel by Car


5. Give a Talk

6. Visit Brewery

7. Have Dinner

8. Go Home

9. Pay Parking

10. Travel by Car

1. Start

2. Get Ready

3. Travel by Car

4. Conference Starts

5. Join Reception

6. Have Dinner

7. Go Home

8. Pay Parking

9. Travel by Car

10. End

Start

Get Ready

Travel by CarTravel by Train

BETA PhD Day Starts

Visit Brewery

Have Dinner

Go Home

Travel by Train Pay for Parking

Travel by Car

End

Give a Talk

StartStart

Get ReadyGet Ready

Travel byTravel by TrainTrain

Travel byTravel by CarCar

Conference StartsConference Starts

Give a TalkGive a Talk

Join ReceptionJoin Reception

Have DinnerHave Dinner

Go HomeGo Home



Pay Pay ParkingParking

EndEnd

Mining Common Constructs

• Sequence• Splits• Joins• Loops• Non-Free Choice• Invisible Tasks• Duplicate Tasks


Get Ready


Defence Starts

Ask Question

Defence Ends

Go Home


Travel by Car

Give a Talk

Have Drinks

Get Get ReadyReady



Defense StartsDefense Starts


Ask QuestionAsk Question

Defense EndsDefense Ends

Go HomeGo Home



Have DrinksHave Drinks




Get Ready


Defence Starts

Ask Question

Defence Ends

Go Home


Travel by Car

Give a Talk

Have Drinks

Get Get ReadyReady







Go HomeGo Home




+ noise in logs!

α-algorithm Basic Idea: 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

AABBAACCBBDDCCDDEEFF

B||CB||CC||BC||B

ABCDABCD

ACBDACBD

EFEF

Basic Idea: Example

Basic Idea: Example

Basic Idea: Footprints

Basic Idea: Patterns

α-algorithm

α-algorithm: Applicative Example










α-algorithm: Exercise

Limitations: short loops of length 1

b>b and not b>b implies bb (impossible!)


Example “Short1”Example “Short1”


a>b and b>a implies a||b and b||a instead of ab and ba


Example “Short2”Example “Short2”

Limitations: non-free-choice nets

Example “nonlocal”Example “nonlocal”

Limitations: invisible tasks

Example “invisible”Example “invisible”




Get Ready


Defence Starts

Ask Question

Defence Ends

Go Home


Travel by Car

Give a Talk

Have Drinks

Get Get ReadyReady







Go HomeGo Home







Get Ready


Defence Starts

Ask Question

Defence Ends

Go Home


Travel by Car

Give a Talk

Have Drinks

Get Get ReadyReady







Go HomeGo Home




+ noise in logs!

Heuristic Miner

Heuristic Miner

Heuristic Miner

Heuristic Miner

Example “heuristic”Example “heuristic”

Heuristic Miner

Example “heuristic”Example “heuristic”




Get Ready


Defence Starts

Ask Question

Defence Ends

Go Home


Travel by Car

Give a Talk

Have Drinks

Get Get ReadyReady







Go HomeGo Home







Get Ready


Defence Starts

Ask Question

Defence Ends

Go Home


Travel by Car

Give a Talk

Have Drinks

Get Get ReadyReady







Go HomeGo Home




+ noise in logs!

Genetic Miner

GPM – Fitness MeasureStart

Get Ready


BETA PhD Day Starts

Visit Brewery

Have Dinner

Go Home


Travel by Car

End

Give a Talk

StartStart

Get ReadyGet Ready





Visit BreweryVisit Brewery


Go HomeGo Home




EndEnd

• Guides the search!

GPM – Fitness Measure

Start

Get Ready


BETA PhD Day Starts

Visit Brewery

Have Dinner

Go Home


Travel by Car

End

Give a Talk

Start

Get Ready

Travel by TrainBETA PhD Day Starts

Visit Brewery

Have Dinner

Go Home

Pay for Parking

Travel by Car

End

Give a Talk

StartStart

Get ReadyGet Ready






Go HomeGo Home


EndEnd


Punish for the amount of enabled tasks during the parsing!

Overgeneral solution

GPM – Fitness Measure

Start

Get Ready


BETA PhD Day Starts

Visit Brewery

Have Dinner

Go Home


Travel by Car

End

Give a Talk

Start

Get Ready

Travel by TrainBETA PhD Day Starts

Visit Brewery

Have Dinner

Go Home

Pay for Parking

Travel by Car

End

Give a Talk

Start

Get Ready


BETA PhD Day Starts

Visit Brewery

Have Dinner

Go Home


Travel by Car

End

Give a Talk

StartStart Start

Get ReadyGet Ready Get Ready

Travel by Train Travel by Car

BETA PhD Day StartsBETA PhD Day Starts BETA PhD Day Starts

Give a Talk

Visit BreweryVisit Brewery Visit Brewery

Have DinnerHave Dinner Have Dinner

Go HomeGo HomeGo Home


Travel by Car

EndEnd End

StartStart

Get ReadyGet Ready

Travel by CarTravel by Car





Go HomeGo Home

Travel by TrainTravel by Train

Travel by CarTravel by Car

Pay ParkingPay Parking

EndEnd

Travel by TrainTravel by Train

Punish for the amount of duplicate tasks with common input/output tasks!

Overspecific solution

Genetic Miner: Crossover

Genetic Miner: Mutation




Get Ready


Defence Starts

Ask Question

Defence Ends

Go Home


Travel by Car

Give a Talk

Have Drinks

Get Get ReadyReady







Go HomeGo Home







Get Ready


Defence Starts

Ask Question

Defence Ends

Go Home


Travel by Car

Give a Talk

Have Drinks

Get Get ReadyReady







Go HomeGo Home




+ noise in logs!

Fuzzy Miner - Motivation

Mine less structured processes!

Fuzzy Miner - Motivation

Fuzzy Miner

Fuzzy Miner

BPI Challenge and … to sum up

Process Mining Control flow process discovery Fabrizio Maria Maggi (based on Process Mining book – Springer copyright 2011 and lecture material by Marlon.

Documents

applicative examplealgorithm

task b case

task c case

example short2limitations

example short1limitations

algorithm basic idea

case x

common inputoutput tasks