Presentation is loading. Please wait.

Presentation is loading. Please wait.

/faculteit technologie management www.processmining.org Genetic Process Mining Ana Karla Alves de Medeiros Eindhoven University of Technology Department.

Published by Modified over 9 years ago

Similar presentations

Presentation on theme: "/faculteit technologie management www.processmining.org Genetic Process Mining Ana Karla Alves de Medeiros Eindhoven University of Technology Department."— Presentation transcript:

1 /faculteit technologie management www.processmining.org Genetic Process Mining Ana Karla Alves de Medeiros Eindhoven University of Technology Department of Information Systems a.k.medeiros@tm.tue.nl

2 /faculteit technologie management www.processmining.org Outline Process Mining –Motivation –Current Techniques –Contribution Genetic Algorithms Experiments and Results Conclusion and Future Work

3 /faculteit technologie management www.processmining.org Outline Process Mining –Motivation –Current Techniques –Contribution Genetic Algorithms Experiments and Results Conclusion and Future Work

4 /faculteit technologie management www.processmining.org Motivation – Typical way to deploy a system 1.Get Ready 2.Travel by Train 3.Beta Event Starts 4.Visit Brewery 5.Have Dinner 6.Go Home 7.Travel by Train 1.Get Ready 2.Travel by Train 3.Beta Event Starts 4.Give a Talk 5.Visit Brewery 6.Have Dinner 7.Go Home 8.Travel by Train

5 /faculteit technologie management www.processmining.org Motivation – Typical way to deploy a system Time consuming –Paper procedures –Meetings Error prone –Different people have different views about a same process –Information about the process may be incomplete

6 /faculteit technologie management www.processmining.org Motivation – More possible cases in the log 1.Get Ready 2.Travel by Train 3.Beta Event Starts 4.Visit Brewery 5.Have Dinner 6.Go Home 7.Travel by Train 1.Get Ready 2.Travel by Train 3.Beta Event Starts 4.Give a Talk 5.Visit Brewery 6.Have Dinner 7.Go Home 8.Travel by Train 1.Get Ready 2.Travel by Car 3.Beta Event Starts 4.Give a Talk 5.Visit Brewery 6.Have Dinner 7.Go Home 8.Pay Parking 9.Travel by Car 1.Get Ready 2.Travel by Car 3.Beta Event Starts 4.Visit Brewery 5.Have Dinner 6.Go Home 7.Pay Parking 8.Travel by Car

7 /faculteit technologie management www.processmining.org Motivation – Process Mining 1.Get Ready 2.Travel by Train 3.Beta Event Starts 4.Visit Brewery 5.Have Dinner 6.Go Home 7.Travel by Train 1.Get Ready 2.Travel by Train 3.Beta Event Starts 4.Give a Talk 5.Visit Brewery 6.Have Dinner 7.Go Home 8.Travel by Train 1.Get Ready 2.Travel by Car 3.Beta Event Starts 4.Give a Talk 5.Visit Brewery 6.Have Dinner 7.Go Home 8.Pay Parking 9.Travel by Car 1.Get Ready 2.Travel by Car 3.Beta Event Starts 4.Visit Brewery 5.Have Dinner 6.Go Home 7.Pay Parking 8.Travel by Car Start Get Ready Travel by Train Train Travel by Car Car Beta Event Starts Give a Talk Visit Brewery Have Dinner Go Home Travel by Train Train Travel by Car Car PayParking End Log MiningTechniques MinedModel

8 /faculteit technologie management www.processmining.org Motivation – Process Mining Before deployment –Objective picture of how the process has been executed After deployment –Feedback mechanism

9 /faculteit technologie management www.processmining.org Current Techniques vs Constructs Sequence Splits Joins Loops Non-free Choice Invisible Tasks Duplicate Tasks Start Get Ready Travel by Train Train Travel by Car Car Beta Event Starts Give a Talk Visit Brewery Have Dinner Go Home Travel by Train Train Travel by Car Car PayParking End

10 /faculteit technologie management www.processmining.org Current Techniques vs Constructs Sequence Splits Joins Loops Non-free Choice Invisible Tasks Duplicate Tasks Start Get Ready Travel by Train Train Travel by Car Car Beta Event Starts Give a Talk Visit Brewery Have Dinner Go Home Travel by Train Train Travel by Car Car PayParking End    1.Get Ready 2.Travel by Car 3.Beta Event Starts 4.Give a Talk 5.Visit Brewery 6.Have Dinner 7.Go Home 8.Pay Parking 9.Travel by Car

11 /faculteit technologie management www.processmining.org Current Techniques vs Constructs Sequence Splits Joins Loops Non-free Choice Invisible Tasks Duplicate Tasks Start Get Ready Travel by Train Train Travel by Car Car Beta Event Starts Give a Talk Visit Brewery Have Dinner Go Home Travel by Train Train Travel by Car Car PayParking End   

12 /faculteit technologie management www.processmining.org Current Techniques vs Constructs Sequence Splits Joins Loops Non-free Choice Invisible Tasks Duplicate Tasks Start Get Ready Travel by Train Train Travel by Car Car Beta Event Starts Give a Talk Visit Brewery Have Dinner Go Home Travel by Train Train Travel by Car Car PayParking End   

13 /faculteit technologie management www.processmining.org Current Techniques vs Constructs: The  -algorithm

14 /faculteit technologie management www.processmining.org Current Techniques Problematic structural constructs –Non-free choice, invisible tasks, duplicate tasks Noise –Wrongly logged traces –Exceptional situations Can we develop a mining algorithm that is able to tackle all structural constructs and noisy logs at the same time?

15 /faculteit technologie management www.processmining.org Outline Process Mining –Motivation –Current Techniques –Contribution Genetic Algorithms Experiments and Results Conclusion and Future Work

16 /faculteit technologie management www.processmining.org Genetic Algorithms –Global approach local optimum global optimum

17 /faculteit technologie management www.processmining.org Genetic Process Mining (GPM) Aim: Use genetic algorithm to tackle non-free choice, invisible tasks, duplicate tasks and noise. Internal Representation Fitness Measure Genetic Operators

18 /faculteit technologie management www.processmining.org Genetic Process Mining (GPM) Demo –Genetic Miner plug-in www.processmining.org –Tool at www.processmining.org

19 /faculteit technologie management www.processmining.org Outline Process Mining –Motivation –Current Techniques –Contribution Genetic Algorithms Experiments Conclusion and Future Work

20 /faculteit technologie management www.processmining.org Experiments Simulation to generate the logs Original Process aaaaaaaaaa aaaaaaaaaa aaaaaaaaaa aaaaa Logs Genetic Miner aaaaaaaaaa aaaaaaaaaa aaaaaaaaaa aaaaa Mined Process Can the mined process generate all the behavior in the log? How close is the behavior of the mined process to the original one?

21 /faculteit technologie management www.processmining.org Outline Process Mining –Motivation –Current Techniques –Contribution Genetic Algorithms Experiments and Results Conclusion and Future Work

22 /faculteit technologie management www.processmining.org Conclusion and Future work Genetic algorithms can be used to mine process models –Global approach –Robust to noise Run more experiments Case study –Do you have real data for us? Write thesis

23 /faculteit technologie management www.processmining.org http://www.processmining.org

Download ppt "/faculteit technologie management www.processmining.org Genetic Process Mining Ana Karla Alves de Medeiros Eindhoven University of Technology Department."

Similar presentations

From Local Patterns to Global Models: Towards Domain Driven Educational Process Mining Nikola Trčka Mykola Pechenizkiy.

From Local Patterns to Global Models: Towards Domain Driven Educational Process Mining Nikola Trčka Mykola Pechenizkiy.
AVATAR: Advanced Telematic Search of Audivisual Contents by Semantic Reasoning Yolanda Blanco Fernández Department of Telematic Engineering University.

AVATAR: Advanced Telematic Search of Audivisual Contents by Semantic Reasoning Yolanda Blanco Fernández Department of Telematic Engineering University.
Jorge Muñoz-Gama Josep Carmona

Jorge Muñoz-Gama Josep Carmona
Sequential Patterns & Process Mining Current State of Research Edgar de Graaf LIACS.

Sequential Patterns & Process Mining Current State of Research Edgar de Graaf LIACS.
/faculteit technologie management 1 Process Mining: Organizational and Conformance Mining Algorithms Ana Karla Alves de Medeiros Ana Karla Alves de Medeiros.

/faculteit technologie management 1 Process Mining: Organizational and Conformance Mining Algorithms Ana Karla Alves de Medeiros Ana Karla Alves de Medeiros.
/faculteit technologie management 1 Process Mining: Control-Flow Mining Algorithms Ana Karla Alves de Medeiros Ana Karla Alves de Medeiros Eindhoven University.

/faculteit technologie management 1 Process Mining: Control-Flow Mining Algorithms Ana Karla Alves de Medeiros Ana Karla Alves de Medeiros Eindhoven University.
The Path to Multi-core Tools Paul Petersen. Multi-coreToolsThePathTo 2 Outline Motivation Where are we now What is easy to do next What is missing.

The Path to Multi-core Tools Paul Petersen. Multi-coreToolsThePathTo 2 Outline Motivation Where are we now What is easy to do next What is missing.
Institute of Intelligent Power Electronics – IPE Page1 Introduction to Basics of Genetic Algorithms Docent Xiao-Zhi Gao Department of Electrical Engineering.

Institute of Intelligent Power Electronics – IPE Page1 Introduction to Basics of Genetic Algorithms Docent Xiao-Zhi Gao Department of Electrical Engineering.
© S. Demeyer, S. Ducasse, O. Nierstrasz Reverse Engineering.1 2. Reverse Engineering What and Why Setting Direction  Most Valuable First First Contact.

© S. Demeyer, S. Ducasse, O. Nierstrasz Reverse Engineering.1 2. Reverse Engineering What and Why Setting Direction  Most Valuable First First Contact.
/faculteit technologie management Genetic Process Mining Ana Karla Medeiros Ton Weijters Wil van der Aalst Eindhoven University of Technology Department.

/faculteit technologie management Genetic Process Mining Ana Karla Medeiros Ton Weijters Wil van der Aalst Eindhoven University of Technology Department.
/faculteit technologie management CPN 2006 Modeling Business Processes with CPN R.S. Mans.

/faculteit technologie management CPN 2006 Modeling Business Processes with CPN R.S. Mans.
Process Mining from discovery to checking Prof.dr.ir. Wil van der Aalst Eindhoven University of Technology, Department of Information Systems, P.O. Box.

Process Mining from discovery to checking Prof.dr.ir. Wil van der Aalst Eindhoven University of Technology, Department of Information Systems, P.O. Box.
Process Mining in CSCW Systems All truths are easy to understand once they are discovered; the point is to discover them. Galileo Galilei (1564 - 1642)

Process Mining in CSCW Systems All truths are easy to understand once they are discovered; the point is to discover them. Galileo Galilei ( )
Mining Social Networks Uncovering interaction patterns in business processes Prof.dr.ir. Wil van der Aalst Eindhoven University of Technology Department.

Mining Social Networks Uncovering interaction patterns in business processes Prof.dr.ir. Wil van der Aalst Eindhoven University of Technology Department.
1 Analysis of workflows a-priori and a-posteriori analysis Wil van der Aalst Eindhoven University of Technology Faculty of Technology Management Department.

1 Analysis of workflows a-priori and a-posteriori analysis Wil van der Aalst Eindhoven University of Technology Faculty of Technology Management Department.
/department of mathematics and computer science Visualization of Transition Systems Hannes Pretorius Visualization Group

/department of mathematics and computer science Visualization of Transition Systems Hannes Pretorius Visualization Group
Business Alignment Using Process Mining as a Tool for Delta Analysis Prof.dr.ir. Wil van der Aalst Eindhoven University of Technology Department of Information.

Business Alignment Using Process Mining as a Tool for Delta Analysis Prof.dr.ir. Wil van der Aalst Eindhoven University of Technology Department of Information.
/faculteit technologie management Dutch-Belgian Database Day 2007 The Challenges of Process Mining A.J.M.M. Weijters (and many others)

/faculteit technologie management Dutch-Belgian Database Day 2007 The Challenges of Process Mining A.J.M.M. Weijters (and many others)
/faculteit technologie management Process Mining and Security: Detecting Anomalous Process Executions and Checking Process Conformance Wil van der Aalst.

/faculteit technologie management Process Mining and Security: Detecting Anomalous Process Executions and Checking Process Conformance Wil van der Aalst.
Discovering Coordination Patterns using Process Mining Prof.dr.ir. Wil van der Aalst Eindhoven University of Technology Department of Information and Technology.

Discovering Coordination Patterns using Process Mining Prof.dr.ir. Wil van der Aalst Eindhoven University of Technology Department of Information and Technology.

Similar presentations

Ads by Google