Process Mining. ^J Springer. Discovery, Conformance and Enhancement of Business Processes. Wil M.R van der Aalst Q UNIVERS1TAT.

Size: px
Start display at page:

Download "Process Mining. ^J Springer. Discovery, Conformance and Enhancement of Business Processes. Wil M.R van der Aalst Q UNIVERS1TAT."

Transcription

1 Wil M.R van der Aalst Process Mining Discovery, Conformance and Enhancement of Business Processes Q UNIVERS1TAT m LIECHTENSTEIN Bibliothek ^J Springer

2 Contents 1 Introduction I 1.1 Data Explosion I 1.2 Limitations of Modeling Process Mining Analyzing an Example Log Play-in, Play-out, and Replay Trends Outlook 23 Part I Preliminaries 2 Process Modeling and Analysis The Art of Modeling Process Models Transition Systems Petri Nets Workflow Nets YAWL Business Process Modeling Notation (BPMN) Event-Driven Process Chains (EPCs) Causal Nets Model-Based Process Analysis Verification Performance Analysis Limitations of Model-Based Analysis 57 3 Data Mining Classification of Data Mining Techniques Data Sets: Instances and Variables Supervised Learning: Classification and Regression Unsupervised Learning: Clustering and Pattern Discovery Decision Tree Learning 64

3 xiv Contents Part II 3.3 -Means Clustering Association Rule Learning Sequence and Episode Mining Sequence Mining Episode Mining Other Approaches Quality of Resulting Models Measuring the Performance of a Classifier Cross-Validalion Occam's Razor 88 From Event Logs to Process Models 4 Getting the Data Data Sources Event Logs XES Flattening Reality into Event Logs Process Discovery: An Introduction Problem Statement A Simple Algorithm for Process Discovery Basic Idea Algorithm Limitations of the or-algorithm Taking the Transactional Life-Cycle into Account Rediscovering Process Models Challenges Representational Bias Noise and Incompleteness Four Competing Quality Criteria Taking the Right 2-D Slice of a 3-D Reality Advanced Process Discovery Techniques Overview Characteristic 1: Representational Bias Characteristic 2: Ability to Deal with Noise Characteristic 3: Completeness Notion Assumed Characteristic 4: Approach Used Heuristic Mining Causal Nets Revisited Learning the Dependency Graph Learning Splits and Joins Genetic Process Mining Region-Based Mining Learning Transition Systems Process Discovery Using State-Based Regions 177

4 Contents xv Process Discovery Using Language-Based Regions Historical Perspective 183 Part III Beyond Process Discovery 7 Conformance Checking Business Alignment and Auditing Token Replay Comparing Footprints Other Applications of Conformance Checking Repairing Models Evaluating Process Discovery Algorithms Connecting Event Log and Process Model Mining Additional Perspectives Perspectives Attributes: A Helicopter View Organizational Mining Social Network Analysis Discovering Organizational Structures Analyzing Resource Behavior Time and Probabilities Decision Mining Bringing It All Together Operational Support Refined Process Mining Framework Cartography Auditing Navigation Online Process Mining Delect Predict Recommend Process Mining Spectrum 258 Part IV Putting Process Mining to Work 10 Tool Support Business Intelligence?, ProM Other Process Mining Tools Outlook Analyzing "Lasagna Processes" Characterization of "Lasagna Processes" Use Cases Approach 282

5 xvi Contents Stage 0: Plan and Justify Stage 1: Extract Stage 2: Create Control-Flow Model and Connect Event Log Stage 3: Create Integrated Process Model Stage 4: Operational Support Applications Process Mining Opportunities per Functional Area Process Mining Opportunities per Sector Two Lasagna Processes Analyzing "Spaghetti Processes" Characterization of "Spaghetti Processes" Approach Applications Process Mining Opportunities for Spaghetti Processes Examples of Spaghetti Processes 310 Part V Reflection 13 Cartography and Navigation Business Process Maps Map Quality Aggregation and Abstraction Seamless Zoom Size, Color, and Layout Customization Process Mining: TomTom for Business Processes? Projecting Dynamic Information on Business Process Maps Arrival Time Prediction Guidance Rather than Control Epilogue Process Mining: A Bridge Between Data Mining and Business Process Management Challenges Start Today! 340 References.341 Index 349

Summary and Outlook. Business Process Intelligence Course Lecture 8. prof.dr.ir. Wil van der Aalst. www.processmining.org

Summary and Outlook. Business Process Intelligence Course Lecture 8. prof.dr.ir. Wil van der Aalst. www.processmining.org Business Process Intelligence Course Lecture 8 Summary and Outlook prof.dr.ir. Wil van der Aalst www.processmining.org Overview Chapter 1 Introduction Part I: Preliminaries Chapter 2 Process Modeling and

More information

Process Mining. Data science in action

Process Mining. Data science in action Process Mining. Data science in action Julia Rudnitckaia Brno, University of Technology, Faculty of Information Technology, irudnickaia@fit.vutbr.cz 1 Abstract. At last decades people have to accumulate

More information

Chapter 12 Analyzing Spaghetti Processes

Chapter 12 Analyzing Spaghetti Processes Chapter 12 Analyzing Spaghetti Processes prof.dr.ir. Wil van der Aalst www.processmining.org Overview Chapter 1 Introduction Part I: Preliminaries Chapter 2 Process Modeling and Analysis Chapter 3 Data

More information

Lluis Belanche + Alfredo Vellido. Intelligent Data Analysis and Data Mining. Data Analysis and Knowledge Discovery

Lluis Belanche + Alfredo Vellido. Intelligent Data Analysis and Data Mining. Data Analysis and Knowledge Discovery Lluis Belanche + Alfredo Vellido Intelligent Data Analysis and Data Mining or Data Analysis and Knowledge Discovery a.k.a. Data Mining II An insider s view Geoff Holmes: WEKA founder Process Mining

More information

Chapter 4 Getting the Data

Chapter 4 Getting the Data Chapter 4 Getting the Data prof.dr.ir. Wil van der Aalst www.processmining.org Overview Chapter 1 Introduction Part I: Preliminaries Chapter 2 Process Modeling and Analysis Chapter 3 Data Mining Part II:

More information

Model Discovery from Motor Claim Process Using Process Mining Technique

Model Discovery from Motor Claim Process Using Process Mining Technique International Journal of Scientific and Research Publications, Volume 3, Issue 1, January 2013 1 Model Discovery from Motor Claim Process Using Process Mining Technique P.V.Kumaraguru *, Dr.S.P.Rajagopalan

More information

Process Mining and Fraud Detection

Process Mining and Fraud Detection Process Mining and Fraud Detection A case study on the theoretical and practical value of using process mining for the detection of fraudulent behavior in the procurement process Masters of Science Thesis

More information

Implementing Heuristic Miner for Different Types of Event Logs

Implementing Heuristic Miner for Different Types of Event Logs Implementing Heuristic Miner for Different Types of Event Logs Angelina Prima Kurniati 1, GunturPrabawa Kusuma 2, GedeAgungAry Wisudiawan 3 1,3 School of Compuing, Telkom University, Indonesia. 2 School

More information

Process Mining Data Science in Action

Process Mining Data Science in Action Process Mining Data Science in Action Wil van der Aalst Scientific director of the DSC/e Dutch Data Science Summit, Eindhoven, 4-5-2014. Process Mining Data Science in Action https://www.coursera.org/course/procmin

More information

Process Modelling from Insurance Event Log

Process Modelling from Insurance Event Log Process Modelling from Insurance Event Log P.V. Kumaraguru Research scholar, Dr.M.G.R Educational and Research Institute University Chennai- 600 095 India Dr. S.P. Rajagopalan Professor Emeritus, Dr. M.G.R

More information

Using Process Mining to Bridge the Gap between BI and BPM

Using Process Mining to Bridge the Gap between BI and BPM Using Process Mining to Bridge the Gap between BI and BPM Wil van der alst Eindhoven University of Technology, The Netherlands Process mining techniques enable process-centric analytics through automated

More information

Analysis of Service Level Agreements using Process Mining techniques

Analysis of Service Level Agreements using Process Mining techniques Analysis of Service Level Agreements using Process Mining techniques CHRISTIAN MAGER University of Applied Sciences Wuerzburg-Schweinfurt Process Mining offers powerful methods to extract knowledge from

More information

Business Process Modeling

Business Process Modeling Business Process Concepts Process Mining Kelly Rosa Braghetto Instituto de Matemática e Estatística Universidade de São Paulo kellyrb@ime.usp.br January 30, 2009 1 / 41 Business Process Concepts Process

More information

Mercy Health System. St. Louis, MO. Process Mining of Clinical Workflows for Quality and Process Improvement

Mercy Health System. St. Louis, MO. Process Mining of Clinical Workflows for Quality and Process Improvement Mercy Health System St. Louis, MO Process Mining of Clinical Workflows for Quality and Process Improvement Paul Helmering, Executive Director, Enterprise Architecture Pete Harrison, Data Analyst, Mercy

More information

CHAPTER 1 INTRODUCTION

CHAPTER 1 INTRODUCTION CHAPTER 1 INTRODUCTION 1.1 Research Motivation In today s modern digital environment with or without our notice we are leaving our digital footprints in various data repositories through our daily activities,

More information

Dotted Chart and Control-Flow Analysis for a Loan Application Process

Dotted Chart and Control-Flow Analysis for a Loan Application Process Dotted Chart and Control-Flow Analysis for a Loan Application Process Thomas Molka 1,2, Wasif Gilani 1 and Xiao-Jun Zeng 2 Business Intelligence Practice, SAP Research, Belfast, UK The University of Manchester,

More information

Feature. Applications of Business Process Analytics and Mining for Internal Control. World

Feature. Applications of Business Process Analytics and Mining for Internal Control. World Feature Filip Caron is a doctoral researcher in the Department of Decision Sciences and Information Management, Information Systems Group, at the Katholieke Universiteit Leuven (Flanders, Belgium). Jan

More information

Process Mining: Making Knowledge Discovery Process Centric

Process Mining: Making Knowledge Discovery Process Centric Process Mining: Making Knowledge Discovery Process Centric Wil van der alst Department of Mathematics and Computer Science Eindhoven University of Technology PO Box 513, 5600 MB, Eindhoven, The Netherlands

More information

Process Mining and Visual Analytics: Breathing Life into Business Process Models

Process Mining and Visual Analytics: Breathing Life into Business Process Models Process Mining and Visual Analytics: Breathing Life into Business Process Models Wil M.P. van der Aalst 1, Massimiliano de Leoni 1, and Arthur H.M. ter Hofstede 1,2 1 Eindhoven University of Technology,

More information

Data Science. Research Theme: Process Mining

Data Science. Research Theme: Process Mining Data Science Research Theme: Process Mining Process mining is a relatively young research discipline that sits between computational intelligence and data mining on the one hand and process modeling and

More information

Using Trace Clustering for Configurable Process Discovery Explained by Event Log Data

Using Trace Clustering for Configurable Process Discovery Explained by Event Log Data Master of Business Information Systems, Department of Mathematics and Computer Science Using Trace Clustering for Configurable Process Discovery Explained by Event Log Data Master Thesis Author: ing. Y.P.J.M.

More information

Combination of Process Mining and Simulation Techniques for Business Process Redesign: A Methodological Approach

Combination of Process Mining and Simulation Techniques for Business Process Redesign: A Methodological Approach Combination of Process Mining and Simulation Techniques for Business Process Redesign: A Methodological Approach Santiago Aguirre, Carlos Parra, and Jorge Alvarado Industrial Engineering Department, Pontificia

More information

ProM 6 Exercises. J.C.A.M. (Joos) Buijs and J.J.C.L. (Jan) Vogelaar {j.c.a.m.buijs,j.j.c.l.vogelaar}@tue.nl. August 2010

ProM 6 Exercises. J.C.A.M. (Joos) Buijs and J.J.C.L. (Jan) Vogelaar {j.c.a.m.buijs,j.j.c.l.vogelaar}@tue.nl. August 2010 ProM 6 Exercises J.C.A.M. (Joos) Buijs and J.J.C.L. (Jan) Vogelaar {j.c.a.m.buijs,j.j.c.l.vogelaar}@tue.nl August 2010 The exercises provided in this section are meant to become more familiar with ProM

More information

Master Thesis September 2010 ALGORITHMS FOR PROCESS CONFORMANCE AND PROCESS REFINEMENT

Master Thesis September 2010 ALGORITHMS FOR PROCESS CONFORMANCE AND PROCESS REFINEMENT Master in Computing Llenguatges i Sistemes Informàtics Master Thesis September 2010 ALGORITHMS FOR PROCESS CONFORMANCE AND PROCESS REFINEMENT Student: Advisor/Director: Jorge Muñoz-Gama Josep Carmona Vargas

More information

WoPeD - An Educational Tool for Workflow Nets

WoPeD - An Educational Tool for Workflow Nets WoPeD - An Educational Tool for Workflow Nets Thomas Freytag, Cooperative State University (DHBW) Karlsruhe, Germany freytag@dhbw-karlsruhe.de Martin Sänger, 1&1 Internet AG, Karlsruhe, Germany m.saenger09@web.de

More information

Process Mining Tools: A Comparative Analysis

Process Mining Tools: A Comparative Analysis EINDHOVEN UNIVERSITY OF TECHNOLOGY Department of Mathematics and Computer Science Process Mining Tools: A Comparative Analysis Irina-Maria Ailenei in partial fulfillment of the requirements for the degree

More information

Translating Message Sequence Charts to other Process Languages using Process Mining

Translating Message Sequence Charts to other Process Languages using Process Mining Translating Message Sequence Charts to other Process Languages using Process Mining Kristian Bisgaard Lassen 1, Boudewijn F. van Dongen 2, and Wil M.P. van der Aalst 2 1 Department of Computer Science,

More information

Handling Big(ger) Logs: Connecting ProM 6 to Apache Hadoop

Handling Big(ger) Logs: Connecting ProM 6 to Apache Hadoop Handling Big(ger) Logs: Connecting ProM 6 to Apache Hadoop Sergio Hernández 1, S.J. van Zelst 2, Joaquín Ezpeleta 1, and Wil M.P. van der Aalst 2 1 Department of Computer Science and Systems Engineering

More information

Chapter 5 Process Discovery: An Introduction

Chapter 5 Process Discovery: An Introduction Chapter 5 Process Discovery: An Introduction Process discovery is one of the most challenging process mining tasks. Based on an event log, a process model is constructed thus capturing the behavior seen

More information

Process Mining Using BPMN: Relating Event Logs and Process Models

Process Mining Using BPMN: Relating Event Logs and Process Models Noname manuscript No. (will be inserted by the editor) Process Mining Using BPMN: Relating Event Logs and Process Models Anna A. Kalenkova W. M. P. van der Aalst Irina A. Lomazova Vladimir A. Rubin Received:

More information

Article. Abstract. This is a pre-print version. For the printed version please refer to www.wisu.de

Article. Abstract. This is a pre-print version. For the printed version please refer to www.wisu.de Article StB Prof. Dr. Nick Gehrke Nordakademie Chair for Information Systems Köllner Chaussee 11 D-25337 Elmshorn nick.gehrke@nordakademie.de Michael Werner, Dipl.-Wirt.-Inf. University of Hamburg Chair

More information

Analyzing a TCP/IP-Protocol with Process Mining Techniques

Analyzing a TCP/IP-Protocol with Process Mining Techniques Analyzing a TCP/IP-Protocol with Process Mining Techniques Christian Wakup 1 and Jörg Desel 2 1 rubecon information technologies GmbH, Germany 2 Fakultät für Mathematik und Informatik, FernUniversität

More information

Mining Configurable Process Models from Collections of Event Logs

Mining Configurable Process Models from Collections of Event Logs Mining Configurable Models from Collections of Event Logs J.C.A.M. Buijs, B.F. van Dongen, and W.M.P. van der Aalst Eindhoven University of Technology, The Netherlands {j.c.a.m.buijs,b.f.v.dongen,w.m.p.v.d.aalst}@tue.nl

More information

Facilitating Business Process Discovery using Email Analysis

Facilitating Business Process Discovery using Email Analysis Facilitating Business Process Discovery using Email Analysis Matin Mavaddat Matin.Mavaddat@live.uwe.ac.uk Stewart Green Stewart.Green Ian Beeson Ian.Beeson Jin Sa Jin.Sa Abstract Extracting business process

More information

Process Mining and Network Analysis

Process Mining and Network Analysis Towards Comprehensive Support for Organizational Mining Minseok Song and Wil M.P. van der Aalst Eindhoven University of Technology P.O.Box 513, NL-5600 MB, Eindhoven, The Netherlands. {m.s.song, w.m.p.v.d.aalst}@tue.nl

More information

Machine Learning and Data Mining. Fundamentals, robotics, recognition

Machine Learning and Data Mining. Fundamentals, robotics, recognition Machine Learning and Data Mining Fundamentals, robotics, recognition Machine Learning, Data Mining, Knowledge Discovery in Data Bases Their mutual relations Data Mining, Knowledge Discovery in Databases,

More information

Discovering Stochastic Petri Nets with Arbitrary Delay Distributions From Event Logs

Discovering Stochastic Petri Nets with Arbitrary Delay Distributions From Event Logs Discovering Stochastic Petri Nets with Arbitrary Delay Distributions From Event Logs Andreas Rogge-Solti 1 and Wil M.P. van der Aalst 2 and Mathias Weske 1 1 Business Process Technology Group, Hasso Plattner

More information

Investigating Clinical Care Pathways Correlated with Outcomes

Investigating Clinical Care Pathways Correlated with Outcomes Investigating Clinical Care Pathways Correlated with Outcomes Geetika T. Lakshmanan, Szabolcs Rozsnyai, Fei Wang IBM T. J. Watson Research Center, NY, USA August 2013 Outline Care Pathways Typical Challenges

More information

Towards a Software Framework for Automatic Business Process Redesign Marwa M.Essam 1, Selma Limam Mansar 2 1

Towards a Software Framework for Automatic Business Process Redesign Marwa M.Essam 1, Selma Limam Mansar 2 1 ACEEE Int. J. on Communication, Vol. 02, No. 03, Nov 2011 Towards a Software Framework for Automatic Business Process Redesign Marwa M.Essam 1, Selma Limam Mansar 2 1 Faculty of Information and Computer

More information

Process Mining Online Assessment Data

Process Mining Online Assessment Data Process Mining Online Assessment Data Mykola Pechenizkiy, Nikola Trčka, Ekaterina Vasilyeva, Wil van der Aalst, Paul De Bra {m.pechenizkiy, e.vasilyeva, n.trcka, w.m.p.v.d.aalst}@tue.nl, debra@win.tue.nl

More information

NAVID KHAJEHZADEH DATA AND PROCESS MINING APPLICATIONS ON A MULTI-CELL FACTORY AUTOMATION TESTBED MASTER OF SCIENCE THESIS

NAVID KHAJEHZADEH DATA AND PROCESS MINING APPLICATIONS ON A MULTI-CELL FACTORY AUTOMATION TESTBED MASTER OF SCIENCE THESIS NAVID KHAJEHZADEH DATA AND PROCESS MINING APPLICATIONS ON A MULTI-CELL FACTORY AUTOMATION TESTBED MASTER OF SCIENCE THESIS Examiner: Professor Jose L. Martinez Lastra Examiner and topic approved in the

More information

Process Mining and the ProM Framework: An Exploratory Survey - Extended report

Process Mining and the ProM Framework: An Exploratory Survey - Extended report Process Mining and the ProM Framework: An Exploratory Survey - Extended report Jan Claes and Geert Poels Department of Management Information Science and Operations Management, Faculty of Economics and

More information

USING PROCESS MINING FOR ITIL ASSESSMENT: A CASE STUDY WITH INCIDENT MANAGEMENT

USING PROCESS MINING FOR ITIL ASSESSMENT: A CASE STUDY WITH INCIDENT MANAGEMENT USING PROCESS MINING FOR ITIL ASSESSMENT: A CASE STUDY WITH INCIDENT MANAGEMENT Diogo R. Ferreira 1,2, Miguel Mira da Silva 1,3 1 IST Technical University of Lisbon, Portugal 2 Organizational Engineering

More information

Dr. Jana Koehler IBM Zurich Research Laboratory

Dr. Jana Koehler IBM Zurich Research Laboratory Precise Modeling of Business Processes with the Business Process Modeling Notation BPMN 2.0 Dr. Jana Koehler IBM Zurich Research Laboratory ZRL BIT at a Glance Computer Science at ZRL: Security/Cryptography

More information

Process Mining and Monitoring Processes and Services: Workshop Report

Process Mining and Monitoring Processes and Services: Workshop Report Process Mining and Monitoring Processes and Services: Workshop Report Wil van der Aalst (editor) Eindhoven University of Technology, P.O.Box 513, NL-5600 MB, Eindhoven, The Netherlands. w.m.p.v.d.aalst@tm.tue.nl

More information

Verifying Business Processes Extracted from E-Commerce Systems Using Dynamic Analysis

Verifying Business Processes Extracted from E-Commerce Systems Using Dynamic Analysis Verifying Business Processes Extracted from E-Commerce Systems Using Dynamic Analysis Derek Foo 1, Jin Guo 2 and Ying Zou 1 Department of Electrical and Computer Engineering 1 School of Computing 2 Queen

More information

Business Process Improvement Framework and Representational Support

Business Process Improvement Framework and Representational Support Business Process Improvement Framework and Representational Support Azeem Lodhi, Veit Köppen, and Gunter Saake Department of Technical and Business Information Systems, Faculty of Computer Science, University

More information

Life-Cycle Support for Staff Assignment Rules in Process-Aware Information Systems

Life-Cycle Support for Staff Assignment Rules in Process-Aware Information Systems Life-Cycle Support for Staff Assignment Rules in Process-Aware Information Systems Stefanie Rinderle-Ma 1,2 and Wil M.P. van der Aalst 2 1 Department Databases and Information Systems, Faculty of Engineering

More information

Generation of a Set of Event Logs with Noise

Generation of a Set of Event Logs with Noise Generation of a Set of Event Logs with Noise Ivan Shugurov International Laboratory of Process-Aware Information Systems National Research University Higher School of Economics 33 Kirpichnaya Str., Moscow,

More information

Trace Clustering in Process Mining

Trace Clustering in Process Mining Trace Clustering in Process Mining M. Song, C.W. Günther, and W.M.P. van der Aalst Eindhoven University of Technology P.O.Box 513, NL-5600 MB, Eindhoven, The Netherlands. {m.s.song,c.w.gunther,w.m.p.v.d.aalst}@tue.nl

More information

Process Mining The influence of big data (and the internet of things) on the supply chain

Process Mining The influence of big data (and the internet of things) on the supply chain September 16, 2015 Process Mining The influence of big data (and the internet of things) on the supply chain Wil van der Aalst www.vdaalst.com @wvdaalst www.processmining.org http://www.engineersjournal.ie/factory-of-thefuture-will-see-merging-of-virtual-and-real-worlds/

More information

Business process measurement - data mining. enn@cc.ttu.ee

Business process measurement - data mining. enn@cc.ttu.ee Business process measurement - data mining. enn@cc.ttu.ee Business process measurement Balanced scorecard Process mining - ProM Äriprotsessi konteksti perspektiiv Clear & measurable goals Effective solutions

More information

Process Mining Framework for Software Processes

Process Mining Framework for Software Processes Process Mining Framework for Software Processes Vladimir Rubin 1,2, Christian W. Günther 1, Wil M.P. van der Aalst 1, Ekkart Kindler 2, Boudewijn F. van Dongen 1, and Wilhelm Schäfer 2 1 Eindhoven University

More information

Index Contents Page No. Introduction . Data Mining & Knowledge Discovery

Index Contents Page No. Introduction . Data Mining & Knowledge Discovery Index Contents Page No. 1. Introduction 1 1.1 Related Research 2 1.2 Objective of Research Work 3 1.3 Why Data Mining is Important 3 1.4 Research Methodology 4 1.5 Research Hypothesis 4 1.6 Scope 5 2.

More information

08 BPMN/1. Software Technology 2. MSc in Communication Sciences 2009-10 Program in Technologies for Human Communication Davide Eynard

08 BPMN/1. Software Technology 2. MSc in Communication Sciences 2009-10 Program in Technologies for Human Communication Davide Eynard MSc in Communication Sciences 2009-10 Program in Technologies for Human Communication Davide Eynard Software Technology 2 08 BPMN/1 2 ntro Sequence of (three?) lessons on BPMN and technologies related

More information

Process-Aware Information Systems: Lessons to be Learned from Process Mining

Process-Aware Information Systems: Lessons to be Learned from Process Mining Process-Aware Information Systems: Lessons to be Learned from Process Mining W.M.P. van der Aalst Department of Mathematics and Computer Science, Eindhoven University of Technology P.O. Box 513, NL-5600

More information

Business Process Mining: From Theory to Practice

Business Process Mining: From Theory to Practice Abstract Business Process Mining: From Theory to Practice C.J. Turner, A. Tiwari, R. A. Olaiya and Y, Xu Purpose - This paper presents a comparison of a number of business process mining tools currently

More information

ProM Framework Tutorial

ProM Framework Tutorial ProM Framework Tutorial Authors: Ana Karla Alves de Medeiros (a.k.medeiros@.tue.nl) A.J.M.M. (Ton) Weijters (a.j.m.m.weijters@tue.nl) Technische Universiteit Eindhoven Eindhoven, The Netherlands February

More information

Bidimensional Process Discovery for Mining BPMN Models

Bidimensional Process Discovery for Mining BPMN Models Bidimensional Process Discovery for Mining BPMN Models Jochen De Weerdt, Seppe K.L.M. vanden Broucke and Filip Caron Department of Decision Sciences and Information Management, KU Leuven Naamsestraat 69,

More information

BIS 3106: Business Process Management. Lecture Two: Modelling the Control-flow Perspective

BIS 3106: Business Process Management. Lecture Two: Modelling the Control-flow Perspective BIS 3106: Business Process Management Lecture Two: Modelling the Control-flow Perspective Makerere University School of Computing and Informatics Technology Department of Computer Science SEM I 2015/2016

More information

Business Process Quality Metrics: Log-based Complexity of Workflow Patterns

Business Process Quality Metrics: Log-based Complexity of Workflow Patterns Business Process Quality Metrics: Log-based Complexity of Workflow Patterns Jorge Cardoso Department of Mathematics and Engineering, University of Madeira, Funchal, Portugal jcardoso@uma.pt Abstract. We

More information

Supporting the BPM lifecycle with FileNet

Supporting the BPM lifecycle with FileNet Supporting the BPM lifecycle with FileNet Mariska Netjes Hajo A. Reijers Wil. M.P. van der Aalst Outline Introduction Evaluation approach Evaluation of FileNet Conclusions Business Process Management Supporting

More information

Business Intelligence and Process Modelling

Business Intelligence and Process Modelling Business Intelligence and Process Modelling F.W. Takes Universiteit Leiden Lecture 7: Network Analytics & Process Modelling Introduction BIPM Lecture 7: Network Analytics & Process Modelling Introduction

More information

Contents. Introduction and System Engineering 1. Introduction 2. Software Process and Methodology 16. System Engineering 53

Contents. Introduction and System Engineering 1. Introduction 2. Software Process and Methodology 16. System Engineering 53 Preface xvi Part I Introduction and System Engineering 1 Chapter 1 Introduction 2 1.1 What Is Software Engineering? 2 1.2 Why Software Engineering? 3 1.3 Software Life-Cycle Activities 4 1.3.1 Software

More information

Structural Detection of Deadlocks in Business Process Models

Structural Detection of Deadlocks in Business Process Models Structural Detection of Deadlocks in Business Process Models Ahmed Awad and Frank Puhlmann Business Process Technology Group Hasso Plattner Institut University of Potsdam, Germany (ahmed.awad,frank.puhlmann)@hpi.uni-potsdam.de

More information

Introduction to Data Mining

Introduction to Data Mining Introduction to Data Mining 1 Why Data Mining? Explosive Growth of Data Data collection and data availability Automated data collection tools, Internet, smartphones, Major sources of abundant data Business:

More information

Fundamentals of Business Process Management

Fundamentals of Business Process Management Marlon Dumas Marcello La Rosa Jan Mendling Hajo A. Reijers Fundamentals of Business Process Management Springer 1 Introduction to Business Process Management 1 1.1 Processes Everywhere 1 1.2 Ingredients

More information

Business Process Modeling

Business Process Modeling Business Process Modeling Organization Who? What? Function When? Process Which? Data / Service / Product 1 BPMN Stands for Business Process Management Notation Graphical notation for specifying Business

More information

Process Mining A Comparative Study

Process Mining A Comparative Study International Journal of Advanced Research in Computer Communication Engineering Process Mining A Comparative Study Asst. Prof. Esmita.P. Gupta M.E. Student, Department of Information Technology, VIT,

More information

An Evaluation of Conceptual Business Process Modelling Languages

An Evaluation of Conceptual Business Process Modelling Languages An Evaluation of Conceptual Business Process Modelling Languages Beate List and Birgit Korherr Women s Postgraduate College for Internet Technologies Institute of Software Technology and Interactive Systems

More information

EMailAnalyzer: An E-Mail Mining Plug-in for the ProM Framework

EMailAnalyzer: An E-Mail Mining Plug-in for the ProM Framework EMailAnalyzer: An E-Mail Mining Plug-in for the ProM Framework Wil M.P. van der Aalst 1 and Andriy Nikolov 2 1 Department of Information Systems, Eindhoven University of Technology, P.O. Box 513, NL-5600

More information

A Software Framework for Risk-Aware Business Process Management

A Software Framework for Risk-Aware Business Process Management A Software Framework for Risk-Aware Business Management Raffaele Conforti 1, Marcello La Rosa 1,2, Arthur H.M. ter Hofstede 1,4, Giancarlo Fortino 3, Massimiliano de Leoni 4, Wil M.P. van der Aalst 4,1,

More information

Introduction to Data Mining and Machine Learning Techniques. Iza Moise, Evangelos Pournaras, Dirk Helbing

Introduction to Data Mining and Machine Learning Techniques. Iza Moise, Evangelos Pournaras, Dirk Helbing Introduction to Data Mining and Machine Learning Techniques Iza Moise, Evangelos Pournaras, Dirk Helbing Iza Moise, Evangelos Pournaras, Dirk Helbing 1 Overview Main principles of data mining Definition

More information

Data Science Betere processen en producten dankzij (Big) data. Wil van der Aalst www.vdaalst.com @wvdaalst www.processmining.org

Data Science Betere processen en producten dankzij (Big) data. Wil van der Aalst www.vdaalst.com @wvdaalst www.processmining.org Data Science Betere processen en producten dankzij (Big) data Wil van der Aalst www.vdaalst.com @wvdaalst www.processmining.org Data Science Center Eindhoven http://www.tue.nl/dsce/ DSC/e: Competences

More information

Data Mining. 1 Introduction 2 Data Mining methods. Alfred Holl Data Mining 1

Data Mining. 1 Introduction 2 Data Mining methods. Alfred Holl Data Mining 1 Data Mining 1 Introduction 2 Data Mining methods Alfred Holl Data Mining 1 1 Introduction 1.1 Motivation 1.2 Goals and problems 1.3 Definitions 1.4 Roots 1.5 Data Mining process 1.6 Epistemological constraints

More information

BUsiness process mining, or process mining in a short

BUsiness process mining, or process mining in a short , July 2-4, 2014, London, U.K. A Process Mining Approach in Software Development and Testing Process: A Case Study Rabia Saylam, Ozgur Koray Sahingoz Abstract Process mining is a relatively new and emerging

More information

Eventifier: Extracting Process Execution Logs from Operational Databases

Eventifier: Extracting Process Execution Logs from Operational Databases Eventifier: Extracting Process Execution Logs from Operational Databases Carlos Rodríguez 1, Robert Engel 2, Galena Kostoska 1, Florian Daniel 1, Fabio Casati 1, and Marco Aimar 3 1 University of Trento,

More information

Nirikshan: Process Mining Software Repositories to Identify Inefficiencies, Imperfections, and Enhance Existing Process Capabilities

Nirikshan: Process Mining Software Repositories to Identify Inefficiencies, Imperfections, and Enhance Existing Process Capabilities Nirikshan: Process Mining Software Repositories to Identify Inefficiencies, Imperfections, and Enhance Existing Process Capabilities Monika Gupta monikag@iiitd.ac.in PhD Advisor: Dr. Ashish Sureka Industry

More information

Process Mining for Electronic Data Interchange

Process Mining for Electronic Data Interchange Process Mining for Electronic Data Interchange R. Engel 1, W. Krathu 1, C. Pichler 2, W. M. P. van der Aalst 3, H. Werthner 1, and M. Zapletal 1 1 Vienna University of Technology, Austria Institute for

More information

The ProM framework: A new era in process mining tool support

The ProM framework: A new era in process mining tool support The ProM framework: A new era in process mining tool support B.F. van Dongen, A.K.A. de Medeiros, H.M.W. Verbeek, A.J.M.M. Weijters, and W.M.P. van der Aalst Department of Technology Management, Eindhoven

More information

Activity Mining for Discovering Software Process Models

Activity Mining for Discovering Software Process Models Activity Mining for Discovering Software Process Models Ekkart Kindler, Vladimir Rubin, Wilhelm Schäfer Software Engineering Group, University of Paderborn, Germany [kindler, vroubine, wilhelm]@uni-paderborn.de

More information

Discovering process models from empirical data

Discovering process models from empirical data Discovering process models from empirical data Laura Măruşter (l.maruster@tm.tue.nl), Ton Weijters (a.j.m.m.weijters@tm.tue.nl) and Wil van der Aalst (w.m.p.aalst@tm.tue.nl) Eindhoven University of Technology,

More information

Decision Mining in Business Processes

Decision Mining in Business Processes Decision Mining in Business Processes A. Rozinat and W.M.P. van der Aalst Department of Technology Management, Eindhoven University of Technology P.O. Box 513, NL-5600 MB, Eindhoven, The Netherlands {a.rozinat,w.m.p.v.d.aalst}@tm.tue.nl

More information

Relational XES: Data Management for Process Mining

Relational XES: Data Management for Process Mining Relational XES: Data Management for Process Mining B.F. van Dongen and Sh. Shabani Department of Mathematics and Computer Science, Eindhoven University of Technology, The Netherlands. B.F.v.Dongen, S.Shabaninejad@tue.nl

More information

Chapter 12 Discovering New Knowledge Data Mining

Chapter 12 Discovering New Knowledge Data Mining Chapter 12 Discovering New Knowledge Data Mining Becerra-Fernandez, et al. -- Knowledge Management 1/e -- 2004 Prentice Hall Additional material 2007 Dekai Wu Chapter Objectives Introduce the student to

More information

EFFECTIVE CONSTRUCTIVE MODELS OF IMPLICIT SELECTION IN BUSINESS PROCESSES. Nataliya Golyan, Vera Golyan, Olga Kalynychenko

EFFECTIVE CONSTRUCTIVE MODELS OF IMPLICIT SELECTION IN BUSINESS PROCESSES. Nataliya Golyan, Vera Golyan, Olga Kalynychenko 380 International Journal Information Theories and Applications, Vol. 18, Number 4, 2011 EFFECTIVE CONSTRUCTIVE MODELS OF IMPLICIT SELECTION IN BUSINESS PROCESSES Nataliya Golyan, Vera Golyan, Olga Kalynychenko

More information

life science data mining

life science data mining life science data mining - '.)'-. < } ti» (>.:>,u» c ~'editors Stephen Wong Harvard Medical School, USA Chung-Sheng Li /BM Thomas J Watson Research Center World Scientific NEW JERSEY LONDON SINGAPORE.

More information

ARIS Design Platform Getting Started with BPM

ARIS Design Platform Getting Started with BPM Rob Davis and Eric Brabander ARIS Design Platform Getting Started with BPM 4y Springer Contents Acknowledgements Foreword xvii xix Chapter 1 An Introduction to BPM 1 1.1 Brief History of Business Process

More information

PRACTICAL DATA MINING IN A LARGE UTILITY COMPANY

PRACTICAL DATA MINING IN A LARGE UTILITY COMPANY QÜESTIIÓ, vol. 25, 3, p. 509-520, 2001 PRACTICAL DATA MINING IN A LARGE UTILITY COMPANY GEORGES HÉBRAIL We present in this paper the main applications of data mining techniques at Electricité de France,

More information

An Introduction to Data Mining. Big Data World. Related Fields and Disciplines. What is Data Mining? 2/12/2015

An Introduction to Data Mining. Big Data World. Related Fields and Disciplines. What is Data Mining? 2/12/2015 An Introduction to Data Mining for Wind Power Management Spring 2015 Big Data World Every minute: Google receives over 4 million search queries Facebook users share almost 2.5 million pieces of content

More information

Database Marketing, Business Intelligence and Knowledge Discovery

Database Marketing, Business Intelligence and Knowledge Discovery Database Marketing, Business Intelligence and Knowledge Discovery Note: Using material from Tan / Steinbach / Kumar (2005) Introduction to Data Mining,, Addison Wesley; and Cios / Pedrycz / Swiniarski

More information

A Business Process Services Portal

A Business Process Services Portal A Business Process Services Portal IBM Research Report RZ 3782 Cédric Favre 1, Zohar Feldman 3, Beat Gfeller 1, Thomas Gschwind 1, Jana Koehler 1, Jochen M. Küster 1, Oleksandr Maistrenko 1, Alexandru

More information

Discovering User Communities in Large Event Logs

Discovering User Communities in Large Event Logs Discovering User Communities in Large Event Logs Diogo R. Ferreira, Cláudia Alves IST Technical University of Lisbon, Portugal {diogo.ferreira,claudia.alves}@ist.utl.pt Abstract. The organizational perspective

More information

Ensemble Learning Better Predictions Through Diversity. Todd Holloway ETech 2008

Ensemble Learning Better Predictions Through Diversity. Todd Holloway ETech 2008 Ensemble Learning Better Predictions Through Diversity Todd Holloway ETech 2008 Outline Building a classifier (a tutorial example) Neighbor method Major ideas and challenges in classification Ensembles

More information

Gunther Ruhe Claes Wohlin. Editors. Software Project. Management in a Changing World. ^ Springer

Gunther Ruhe Claes Wohlin. Editors. Software Project. Management in a Changing World. ^ Springer Gunther Ruhe Claes Wohlin Editors Software Project Management in a Changing World ^ Springer Contents 1 Software Project Management: Setting the Context 1 1.1 Motivation 1 1.2 Characteristics of Software

More information

BPMN PATTERNS USED IN MANAGEMENT INFORMATION SYSTEMS

BPMN PATTERNS USED IN MANAGEMENT INFORMATION SYSTEMS BPMN PATTERNS USED IN MANAGEMENT INFORMATION SYSTEMS Gabriel Cozgarea 1 Adrian Cozgarea 2 ABSTRACT: Business Process Modeling Notation (BPMN) is a graphical standard in which controls and activities can

More information

Federico Rajola. Customer Relationship. Management in the. Financial Industry. Organizational Processes and. Technology Innovation.

Federico Rajola. Customer Relationship. Management in the. Financial Industry. Organizational Processes and. Technology Innovation. Federico Rajola Customer Relationship Management in the Financial Industry Organizational Processes and Technology Innovation Second edition ^ Springer Contents 1 Introduction 1 1.1 Identification and

More information

Modeling and Analysis of Incoming Raw Materials Business Process: A Process Mining Approach

Modeling and Analysis of Incoming Raw Materials Business Process: A Process Mining Approach Modeling and Analysis of Incoming Raw Materials Business Process: A Process Mining Approach Mahendrawathi Er*, Hanim Maria Astuti, Dita Pramitasari Information Systems Department, Faculty of Information

More information

Software Visualization and Model Generation

Software Visualization and Model Generation Software Visualization and Model Generation Erik Doernenburg Software Developer ThoughtWorks, Inc. Gregor Hohpe Software Engineer Google, Inc. Where are the most defects? 2006 Erik Doernenburg & Gregor

More information

ProM 6 Tutorial. H.M.W. (Eric) Verbeek mailto:h.m.w.verbeek@tue.nl R. P. Jagadeesh Chandra Bose mailto:j.c.b.rantham.prabhakara@tue.

ProM 6 Tutorial. H.M.W. (Eric) Verbeek mailto:h.m.w.verbeek@tue.nl R. P. Jagadeesh Chandra Bose mailto:j.c.b.rantham.prabhakara@tue. ProM 6 Tutorial H.M.W. (Eric) Verbeek mailto:h.m.w.verbeek@tue.nl R. P. Jagadeesh Chandra Bose mailto:j.c.b.rantham.prabhakara@tue.nl August 2010 1 Introduction This document shows how to use ProM 6 to

More information