Process Mining An index to the state of the art and an outline of open research challenges at DIIAG

Size: px
Start display at page:

Download "Process Mining An index to the state of the art and an outline of open research challenges at DIIAG"

Transcription

1 An index to the state of the art and an outline of open research challenges at DIIAG Claudio Di Ciccio, Massimo Mecella Seminars in Software and Services for the Information Society Rome, 2012, May the 7 th

2 Definition [Aalst2011.book], also referred to as Workflow Mining, is the set of techniques that allow the extraction of process descriptions, stemming from a set of recorded real executions (logs). ProM [AalstEtAl2009] is one of the most used plugin based software environment for implementing workflow mining (and more) techniques. The new version 6.0 is available for download at P. 2

3 Definition involves: Process discovery Control flow mining, organizational mining, decision mining; workflow Conformance checking Operational support We will focus on the control flow mining Many control flow mining algorithms proposed α [AalstEtAl2004] and α ++ [WenEtAl2007] Fuzzy [GüntherAalst2007] Heuristic [WeijtersEtAl2001] Genetic [MedeirosEtAl2007] Two-step [AalstEtAl2010] P. 3

4 Further reading The rest of the lesson is based on the following material: Van der Aalst, W. M. P.: Process Discovery: An Introduction Available at process_mining_chapter_05_process_discovery.pdf From the teaching material for [Aalst2011.book] De Medeiros, A. K. A.: : Control-Flow Mining Algorithms Available at lecture3_controlflowminingalgorithms.ppt P. 4

5 A different context (1) Artful processes and knowledge workers Artful processes [HillEtAl06] informal processes typically carried out by those people whose work is mental rather than physical (managers, professors, researchers, engineers, etc.) knowledge workers [ACTIVE09] Knowledge workers create artful processes on the fly Though artful processes are frequently repeated, they are not exactly reproducible, even by their originators, nor can they be easily shared. P. 5

6 A different context (2) conversations In collaborative contexts, knowledge workers share their information and outcomes with other knowledge workers E.g., a software development mgr. Typically, by means of several conversations conversations are actual traces of running processes that knowledge workers adhere to P. 6

7 A different context (3) Processes from conversations From the collection of messages, you can extract the processes that lay behind Related conversations are traces of their runs Valuable advantages for users Automated discovery of formal representations with no effort for knowledge workers Tidy organization for naïve best practices kept only in mind Opportunity to share and compare the knowledge on methodologies Automated discovery of bottlenecks, delays, structural defects from the analysis of previous runs conversations are a kind of semi-structured text this approach is not tailored to the electronic mail it can be extended to the analysis of other semi-structured texts P. 7

8 A different context (4) Some areas of applicability Personal information management (PIM) how to organize one s own activities, contacts, etc. through the usage of software Information warfare in supporting anti-crime intelligence agencies Enterprise engineering for knowledge-heavy industries, where preserving documents making up product data is not enough ehealth for the automatic discovery of medical treatment procedures on top of patient health records P. 8

9 MailOfMine What is MailOfMine? MailOfMine is the approach and the implementation of a collection of techniques, the aim of which is to is to automatically build, on top of a collection of messages, a set of workflow models that represent the artful processes laying behind the knowledge workers activities. [DiCiccioEtAl11] [DiCiccioMecella12] [DiCiccioMecella/TR12] P. 9

10 On the visualization of processes The imperative model Represents the whole process at once The most used notation is based on a subclass of Petri Nets (namely, the Workflow Nets) P. 10

11 On the visualization of processes The declarative model If A is performed, B must be perfomed, no matter before or afterwards (responded existence) Rather than using a procedural language for expressing the allowed sequence of activities, it is based on the description of workflows through the usage of constraints the idea is that every task can be performed, except the ones which do not respect such constraints this technique fits with processes that are highly flexible and subject to changes, such as artful processes The notation here is based on [AalstEtAl06, MaggiEtAl11] (DecSerFlow, Declare) Whenever B is performed, C must be performed afterwards and B can not be repeated until C is done (alternate response) P. 11

12 On the visualization of processes Imperative vs declarative Declarative Imperative Declarative models work better in presence of a partial specification of the process scheme P. 12

13 Declare constraint templates Existence templates Existence(n, A) Activity A occurs at least n times in the process instance BCAAC BCAAAC BCAC (for n = 2) Absence(A) Activity A does not occur in the process instance BCC BCAC Absence(n+1, A) Activity A occurs at most n+1 times in the process instance BCAAC BCAC BCC (for n = 2) Exactly(n, A) Activity A occurs exactly n times in the process instance BCAAC BCAAAC BCAC (for n = 2) Init(A) Activity A is the first to occur in each process instance BCAAC ACAAAC BCC P. 13

14 Declare constraint templates Relation templates RespondedExistence(A, B) If A occurs in the process instance, then B occurs as well CAC CAACB BCAC BCC Response(A, B) If A occurs in the process instance, then B occurs after A BCAAC CAACB CAC BCC AlternateResponse(A, B) Each time A occurs in the process instance, then B occurs afterwards, before A recurs BCAAC CAACB CACB CABCA BCC CACBBAB ChainResponse(A, B) Each time A occurs in the process instance, then B occurs immediately afterwards BCAAC BCAABC BCABABC P. 14

15 Declare constraint templates Relation templates RespondedExistence(B, A) If B occurs in the process instance, then A occurs as well CAC CAACB BCAC BCC Precedence(A, B) B occurs in the process instance only if preceded by A BCAAC CAACB CAC BCC AlternatePrecedence(A, B) Each time B occurs in the process instance, it is preceded by A and no other B can recur in between BCAAC CAACB CACB CABCA BCC CACBAB ChainPrecedence(A, B) Each time B occurs in the process instance, then B occurs immediately beforehand BCAAC BCAABC CABABCA P. 15

16 Declare constraint templates Relation templates CoExistence(A, B) If B occurs in the process instance, then A occurs, and viceversa CAC CAACB BCAC BCC Succession(A, B) A occurs if and only if it is followed by B in the process instance BCAAC CAACB CAC BCC AlternateSuccession(A, B) A and B occur in the process instance if and only if the latter follows the former, and they alternate each other in the trace BCAAC CAACB CACB CABCA BCC CACBAB ChainSuccession(A, B) A and B occur in the process instance if and only if the latter immediately follows the former BCAAC BCAABC CABABC P. 16

17 Declare constraint templates Negative relation templates NotCoExistence(A, B) A and B never occur together in the process instance CAC CAACB BCAC BCC NotSuccession(A, B) A can never occur before B in the process instance BCAAC CAACB CAC BCC NotChainSuccession(A, B) A and B occur in the process instance if and only if the latter does not immediately follows the former BCAAC BCAABC CBACBA P. 17

18 Relation constraint templates subsumption Constraint templates are not independent of each other P. 18

19 Relation constraint templates subsumption Constraint templates are not independent of each other E.g., A trace like ABABCABCC satisfies (w.r.t. A and B): RespondedExistence(A, B), RespondedExistence(B, A), CoExistence(A, B), CoExistence(B, A), Response(A, B), AlternateResponse(A, B), ChainResponse(A, B), Precedence(A, B), AlternatePrecedence(A, B), ChainPrecedence(A, B), Succession(A, B), AlternateSuccession(A, B), ChainSuccession(A, B) The mining algorithm would show the most strict constraint only (ChainSuccession(A, B)) MINERful, the mining algorithm of MailOfMine, faces this unresolved issue P. 19

20 MINERful The declarative workflow mining algorithm of MailOfMine Key idea: building a knowledge base with local and global statistics on the mutual order of appearance of events for further fast querying Performances: the algorithm is proven to be fast (over 12m events processed in less than 170 secs.) Asymptotically: linear in the number of the traces quadratic in the number of events per trace i.e., polynomial in the input size linear in the number of constraint templates See [DiCiccioMecella/TR12] for further reading P. 20

21 LTL semantics ConDec, DecSerFlow and Declare adopt Lineartime Temporal Logic (LTL) for expressing the semantics of the constraint templates. See [AalstEtAl06, MaggiEtAl11] for further reading Van der Aalst, W. M. P. : Auditing 2.0 Using to Support Tomorrow's Auditor Available at process-mining-and-auditing-siks-course wvda.pdf See slides P. 21

22 On the representation of artful process schemata Regular grammars expressing declarative workflows In MailOfMine, each constraint in the set which can be used to define an artful mined process is expressible through regular grammars, where: activities are terminal characters, building blocks of constraints on tasks; constraints are regular expressions, equivalent to regular grammars; the process scheme is the intersection of constraints defined on top of activities. The process scheme defines a Process Describing Grammar (PDG) P. 22

23 On the usage of regular grammars The rationale: why not LTL for declarative workflows? Temporal logic is a formalism for describing sequences of transitions between states in a reactive system Linear Temporal Logic (LTL, [Pnueli77]) describes events along a single computation path LTL formulæ are verified over semi-infinite runs defined over Kripke structures They are good for automatically checking the correct work of circuits or server programs Not for human processes which have both a starting point and an end In the long run, we are all dead ' (John Maynard Keynes) Regular grammars are verified by Finite State Automata working with less complex algorithms, in terms of computational effort A PDG describes the language spoken by collaborative organisms in terms of activities P. 23

24 On the usage of regular grammars Constraint templates as regular expressions P. 24

25 On the visualization of processes An example of DecSerFlow [VanDerAalstEtAl06] notation You could even start from here No, it is not the initial action You might want to run a legal trace like this: a3, a3, a3, a2, a2, a3, a4, a5, a6, a7, a6, a5 What we want to state here is that such a notation is probably not quite intuitive P. 25

26 On the visualization of processes Our proposal We do not consider a static graph-based global representation alone the best suitable solution. A graphical representation, easy to understand at a first glimpse, must be used. Idea: when presenting the process schema (static view): 1) a local view on tasks/activities, showing related constraints only; 2) a global view on the process, either: a) basic (less information, less symbols), or b) extended (more information, more symbols, extending (a)); (2) can work as a kind of navigation map for (1) when presenting the running instance (dynamic view): a dynamic interactive trace representation diagram, based on the local static view notation. See [DiCiccioEtAl2011] for further reading P. 26

27 On the visualization of processes Introducing the new local view: the rationale P. 27

28 On the visualization of constraints The static local view: some examples P. 28

29 On the representation of processes The static global view Basic Extended P. 29

30 A GUI sketch Local and global views together P. 30

31 On the representation of constraints Dynamic view P. 31

32 Open challenges Your contribution is welcome Event frequency handling in MINERful Error injection and robustness testing/improving Auto-thresholding Definition of a basis for declarative processes Graphical model for declarative processes in MailOfMine Implementation and usability testing Auto-refactoring of the dynamic view Refactoring in case of user-driven deviations from the process model P. 32

33 References Cited articles and resources, in order of appearance [Aalst2011.book] van der Aalst, W.M.P.: : Discovery, Conformance and Enhancement of Business Processes. Springer (2011). [AalstEtAl2009] van der Aalst, W.M.P., van Dongen, B.F., Güther, C.W., Rozinat, A., Verbeek, E., Weijters, T.: Prom: The process mining toolkit. In de Medeiros, A.K.A., Weber, B., eds.: BPM (Demos). Volume 489 of CEUR Workshop Proceedings., CEUR-WS.org (2009) [AalstEtAl2004] van der Aalst, W.M.P., Weijters, T., Maruster, L.: Workflow mining: Discovering process models from event logs. IEEE Trans. Knowl. Data Eng. 16(9) (2004) [WenEtAl2007] Wen, L., van der Aalst, W.M.P., Wang, J., Sun, J.: Mining process models with non-free-choice constructs. Data Min. Knowl. Discov. 15(2) (2007) [GüntherEtAl2007] Günther, C.W., van der Aalst, W.M.P.: Fuzzy Mining - Adaptive Process Simplification Based on Multi-perspective Metrics. BPM 2007: [WeijtersEtAl2001] Weijters, A., van der Aalst, W.: Rediscovering workflow models from event-based data using little thumb. Integrated Computer-Aided Engineering 10 (2001) [MedeirosEtAl2007] Medeiros, A.K., Weijters, A.J., Aalst, W.M.: Genetic process mining: an experi- mental evaluation. Data Min. Knowl. Discov. 14(2) (2007) [AalstEtAl2010] van der Aalst, W., Rubin, V., Verbeek, H., van Dongen, B., Kindler, E., Gnther, C.: Process mining: a two-step approach to balance between underfitting and overfitting. Software and Systems Modeling 9 (2010) /s z. P. 33

34 References Cited articles and resources, in order of appearance [HillEtAl06] Hill, C., Yates, R., Jones, C., Kogan, S.L.: Beyond predictable workflows: Enhancing productivity in artful business processes. IBM Systems Journal 45(4), (2006) [ACTIVE09] Warren, P., Kings, N., et al.: Improving knowledge worker productivity - the active integrated approach. BT Technology Journal 26(2), (2009) [DiCiccioEtAl11] Di Ciccio, C., Mecella, M., Catarci, T.: Representing and Visualizing Mined Artful Processes in MailOfMine. USAB 2011:83-94 [DiCiccioMecella12] Di Ciccio, C., Mecella,M.: Mining constraints for artful processes. In W. Abramowicz, D. Kriksciuniene, V.S., ed.: 15th International Conference on Business Information Systems. Volume 117 of Lecture Notes in Business Information Processing., Springer (2012) (to appear). [DiCiccioMecella/TR12] Di Ciccio, C., Mecella, M.: MINERful, a mining algorithm for declarative process constraints in MailOfMine. Technical report, Dipartimento di Ingegneria Infor- matica, Automatica e Gestionale Antonio Ruberti SAPIENZA, Universita` di Roma (2012). [AalstEtAl06] van der Aalst, W.M.P., Pesic, M.: Decserflow: Towards a truly declarative service flow language. Proc. WS-FM 2006 [MaggiEtAl11] Maggi, F.M., Mooij, A.J., van der Aalst, W.M.P.: User-guided discovery of declar- ative process models. In: CIDM, IEEE (2011) [Pnueli77] Pnueli, A.: The Temporal Logic of Programs. Proc. 18th Annual Symposium on Foundations of Software Technology and Theoretical Computer Science, 1977 P. 34

Process Mining An index to the state of the art and an outline of open research challenges at DIAG

Process Mining An index to the state of the art and an outline of open research challenges at DIAG An index to the state of the art and an outline of open research challenges at DIAG Claudio Di Ciccio, Massimo Mecella Seminars in Software and Services for the Information Society Definition [Aalst2011.book],

More information

Mining Constraints for Ar.ul Processes

Mining Constraints for Ar.ul Processes Mining Constraints for Ar.ul Processes Claudio Di Ciccio and Massimo Mecella Claudio Di Ciccio (cdc@dis.uniroma1.it) 15 th Interna?onal Conference on Business Informa?on Systems (BIS 2012) Tuesday, May

More information

Knowledge-intensive Processes: An Overview of Contemporary Approaches Claudio Di Ciccio, Andrea Marrella and Alessandro Russo

Knowledge-intensive Processes: An Overview of Contemporary Approaches Claudio Di Ciccio, Andrea Marrella and Alessandro Russo Knowledge-intensive Processes: An Overview of Contemporary Approaches Claudio Di Ciccio, Andrea Marrella and Alessandro Russo Claudio Di Ciccio (cdc@dis.uniroma1.it) 1 st International Workshop on Knowledge-intensive

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

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

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

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

Efficient Discovery of Understandable Declarative Process Models from Event Logs

Efficient Discovery of Understandable Declarative Process Models from Event Logs Efficient Discovery of Understandable Declarative Process Models from Event Logs Fabrizio M. Maggi, R.P. Jagadeesh Chandra Bose, and Wil M.P. van der Aalst Eindhoven University of Technology, The Netherlands.

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

Replaying History. prof.dr.ir. Wil van der Aalst www.processmining.org

Replaying History. prof.dr.ir. Wil van der Aalst www.processmining.org Replaying History prof.dr.ir. Wil van der Aalst www.processmining.org Growth of data PAGE 1 Process Mining: Linking events to models PAGE 2 Where did we apply process mining? Municipalities (e.g., Alkmaar,

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

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

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

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

REFlex: an entire solution to business process modeling

REFlex: an entire solution to business process modeling REFlex: an entire solution to business process modeling Renata M. de Carvalho and Natália C. Silva 1 University of Quebec at Montreal, LATECE Laboratory, Canada, renatawm@gmail.com 2 C.E.S.A.R - Recife

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

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

Configuring IBM WebSphere Monitor for Process Mining

Configuring IBM WebSphere Monitor for Process Mining Configuring IBM WebSphere Monitor for Process Mining H.M.W. Verbeek and W.M.P. van der Aalst Technische Universiteit Eindhoven Department of Mathematics and Computer Science P.O. Box 513, 5600 MB Eindhoven,

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

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

Conformance Checking of RBAC Policies in Process-Aware Information Systems

Conformance Checking of RBAC Policies in Process-Aware Information Systems Conformance Checking of RBAC Policies in Process-Aware Information Systems Anne Baumgrass 1, Thomas Baier 2, Jan Mendling 2, and Mark Strembeck 1 1 Institute of Information Systems and New Media Vienna

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

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

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

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

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

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

Process Mining. ^J Springer. Discovery, Conformance and Enhancement of Business Processes. Wil M.R van der Aalst Q UNIVERS1TAT. Wil M.R van der Aalst Process Mining Discovery, Conformance and Enhancement of Business Processes Q UNIVERS1TAT m LIECHTENSTEIN Bibliothek ^J Springer Contents 1 Introduction I 1.1 Data Explosion I 1.2

More information

Towards an Evaluation Framework for Process Mining Algorithms

Towards an Evaluation Framework for Process Mining Algorithms Towards an Evaluation Framework for Process Mining Algorithms A. Rozinat, A.K. Alves de Medeiros, C.W. Günther, A.J.M.M. Weijters, and W.M.P. van der Aalst Eindhoven University of Technology P.O. Box 513,

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

Using Semantic Lifting for improving Process Mining: a Data Loss Prevention System case study

Using Semantic Lifting for improving Process Mining: a Data Loss Prevention System case study Using Semantic Lifting for improving Process Mining: a Data Loss Prevention System case study Antonia Azzini, Chiara Braghin, Ernesto Damiani, Francesco Zavatarelli Dipartimento di Informatica Università

More information

Formal Modeling and Analysis by Simulation of Data Paths in Digital Document Printers

Formal Modeling and Analysis by Simulation of Data Paths in Digital Document Printers Formal Modeling and Analysis by Simulation of Data Paths in Digital Document Printers Venkatesh Kannan, Wil M.P. van der Aalst, and Marc Voorhoeve Department of Mathematics and Computer Science, Eindhoven

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

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

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

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

Aligning Event Logs and Declarative Process Models for Conformance Checking

Aligning Event Logs and Declarative Process Models for Conformance Checking Aligning Event Logs and Declarative Process Models for Conformance Checking Massimiliano de Leoni, Fabrizio M. Maggi, and Wil M. P. van der Aalst Eindhoven University of Technology, Eindhoven, The Netherlands

More information

Separating Compliance Management and Business Process Management

Separating Compliance Management and Business Process Management Separating Compliance Management and Business Process Management Elham Ramezani 1, Dirk Fahland 2, Jan Martijn van der Werf 2, and Peter Mattheis 1 1 Hochschule Furtwangen, Germany (ramezani Peter.Mattheis)@hs-furtwangen.de

More information

CPN Tools 4: A Process Modeling Tool Combining Declarative and Imperative Paradigms

CPN Tools 4: A Process Modeling Tool Combining Declarative and Imperative Paradigms CPN Tools 4: A Process Modeling Tool Combining Declarative and Imperative Paradigms Michael Westergaard 1,2 and Tijs Slaats 3,4 1 Department of Mathematics and Computer Science, Eindhoven University of

More information

On the Modeling and Verification of Security-Aware and Process-Aware Information Systems

On the Modeling and Verification of Security-Aware and Process-Aware Information Systems On the Modeling and Verification of Security-Aware and Process-Aware Information Systems 29 August 2011 What are workflows to us? Plans or schedules that map users or resources to tasks Such mappings may

More information

Application of Process Mining in Healthcare A Case Study in a Dutch Hospital

Application of Process Mining in Healthcare A Case Study in a Dutch Hospital Application of Process Mining in Healthcare A Case Study in a Dutch Hospital R.S. Mans 1, M.H. Schonenberg 1, M. Song 1, W.M.P. van der Aalst 1, and P.J.M. Bakker 2 1 Department of Information Systems

More information

Process mining challenges in hospital information systems

Process mining challenges in hospital information systems Proceedings of the Federated Conference on Computer Science and Information Systems pp. 1135 1140 ISBN 978-83-60810-51-4 Process mining challenges in hospital information systems Payam Homayounfar Wrocław

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

BPIC 2014: Insights from the Analysis of Rabobank Service Desk Processes

BPIC 2014: Insights from the Analysis of Rabobank Service Desk Processes BPIC 2014: Insights from the Analysis of Rabobank Service Desk Processes Bruna Christina P. Brandão, Guilherme Neves Lopes, Pedro Henrique P. Richetti Department of Applied Informatics - Federal University

More information

The Research on the Usage of Business Process Mining in the Implementation of BPR

The Research on the Usage of Business Process Mining in the Implementation of BPR 2007 IFIP International Conference on Network and Parallel Computing - Workshops The Research on Usage of Business Process Mining in Implementation of BPR XIE Yi wu 1, LI Xiao wan 1, Chen Yan 2 (1.School

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

Towards Cross-Organizational Process Mining in Collections of Process Models and their Executions

Towards Cross-Organizational Process Mining in Collections of Process Models and their Executions Towards Cross-Organizational Process Mining in Collections of Process Models and their Executions J.C.A.M. Buijs, B.F. van Dongen, W.M.P. van der Aalst Department of Mathematics and Computer Science, Eindhoven

More information

Online Compliance Monitoring of Service Landscapes

Online Compliance Monitoring of Service Landscapes Online Compliance Monitoring of Service Landscapes J.M.E.M. van der Werf 1 and H.M.W. Verbeek 2 1 Department of Information and Computing Science, Utrecht University, The Netherlands J.M.E.M.vanderWerf@UU.nl

More information

A Declarative Approach for Flexible Business Processes Management

A Declarative Approach for Flexible Business Processes Management A Declarative Approach for Flexible Business Processes Management M. Pesic and W.M.P. van der Aalst Department of Technology Management, Eindhoven University of Technology, P.O.Box 513, NL-5600 MB, Eindhoven,

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 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

PLG: a Framework for the Generation of Business Process Models and their Execution Logs

PLG: a Framework for the Generation of Business Process Models and their Execution Logs PLG: a Framework for the Generation of Business Process Models and their Execution Logs Andrea Burattin and Alessandro Sperduti Department of Pure and Applied Mathematics University of Padua, Italy {burattin,sperduti}@math.unipd.it

More information

Discovering Process Models from Unlabelled Event Logs

Discovering Process Models from Unlabelled Event Logs Discovering Process Models from Unlabelled Event Logs Diogo R. Ferreira 1 and Daniel Gillblad 2 1 IST Technical University of Lisbon 2 Swedish Institute of Computer Science (SICS) diogo.ferreira@ist.utl.pt,

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

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

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

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

Discovering Data-Aware Declarative Process Models from Event Logs

Discovering Data-Aware Declarative Process Models from Event Logs Discovering Data-Aware Declarative Process Models from Event Logs Fabrizio M. Maggi 1, Marlon Dumas 1, Luciano García-añuelos 1, and Marco Montali 2 1 University of Tartu, Estonia {f.m.maggi, marlon.dumas,

More information

A Research Article on Data Mining in Addition to Process Mining: Similarities and Dissimilarities

A Research Article on Data Mining in Addition to Process Mining: Similarities and Dissimilarities A Research Article on Data Mining in Addition to Process Mining: Similarities and Dissimilarities S. Sowjanya Chintalapati 1, Ch.G.V.N.Prasad 2, J. Sowjanya 3, R.Vineela 4 1, 3, 4 Assistant Professor,

More information

An Outlook on Semantic Business Process Mining and Monitoring

An Outlook on Semantic Business Process Mining and Monitoring An Outlook on Semantic Business Process Mining and Monitoring A.K. Alves de Medeiros 1,C.Pedrinaci 2, W.M.P. van der Aalst 1, J. Domingue 2,M.Song 1,A.Rozinat 1,B.Norton 2, and L. Cabral 2 1 Eindhoven

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

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

Business Process Measurement in small enterprises after the installation of an ERP software.

Business Process Measurement in small enterprises after the installation of an ERP software. Business Process Measurement in small enterprises after the installation of an ERP software. Stefano Siccardi and Claudia Sebastiani CQ Creativiquadrati snc, via Tadino 60, Milano, Italy http://www.creativiquadrati.it

More information

ERP Event Log Preprocessing: Timestamps vs. Accounting Logic

ERP Event Log Preprocessing: Timestamps vs. Accounting Logic ERP Event Log Preprocessing: Timestamps vs. Accounting Logic Niels Mueller-Wickop and Martin Schultz Chair for Information Systems, University of Hamburg, Hamburg, Germany {niels.mueller-wickop,martin.schultz}@wiso.uni-hamburg.de

More information

Process Mining in Big Data Scenario

Process Mining in Big Data Scenario Process Mining in Big Data Scenario Antonia Azzini, Ernesto Damiani SESAR Lab - Dipartimento di Informatica Università degli Studi di Milano, Italy antonia.azzini,ernesto.damiani@unimi.it Abstract. In

More information

Tilburg University. Publication date: 2010. Link to publication

Tilburg University. Publication date: 2010. Link to publication Tilburg University On the formal specification of business contracts and regulatory compliance Elgammal, Onbekend; Türetken, O.; van den Heuvel, Willem-Jan; Papazoglou, Mike Published in: Proceedings of

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

Compliance Analysis in IT Service Management Systems. Master Thesis

Compliance Analysis in IT Service Management Systems. Master Thesis Compliance Analysis in IT Service Management Systems Master Thesis IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE (M.Sc.) IN INFORMATION SYSTEMS AT THE SCHOOL OF BUSINESS

More information

CCaaS: Online Conformance Checking as a Service

CCaaS: Online Conformance Checking as a Service CCaaS: Online Conformance Checking as a Service Ingo Weber 1, Andreas Rogge-Solti 2, Chao Li 1, and Jan Mendling 2 1 NICTA, Sydney, Australia firstname.lastname@nicta.com.au 2 Wirtschaftsuniversität Wien,

More information

EMiT: A process mining tool

EMiT: A process mining tool EMiT: A process mining tool B.F. van Dongen 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. b.f.v.dongen@tue.nl

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

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

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

Improving Business Process Models with Agent-based Simulation and Process Mining

Improving Business Process Models with Agent-based Simulation and Process Mining Improving Business Process Models with Agent-based Simulation and Process Mining Fernando Szimanski 1, Célia G. Ralha 1, Gerd Wagner 2, and Diogo R. Ferreira 3 1 University of Brasília, Brazil fszimanski@gmail.com,

More information

B. Majeed British Telecom, Computational Intelligence Group, Ipswich, UK

B. Majeed British Telecom, Computational Intelligence Group, Ipswich, UK The current issue and full text archive of this journal is available at wwwemeraldinsightcom/1463-7154htm A review of business process mining: state-of-the-art and future trends A Tiwari and CJ Turner

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

SOFTWARE PROCESS MINING

SOFTWARE PROCESS MINING SOFTWARE PROCESS MINING DR. VLADIMIR RUBIN LEAD IT ARCHITECT & CONSULTANT @ DR. RUBIN IT CONSULTING LEAD RESEARCH FELLOW @ PAIS LAB / HSE ANNOTATION Nowadays, in the era of social, mobile and cloud computing,

More information

Conformance Checking of Interacting Processes With Overlapping Instances

Conformance Checking of Interacting Processes With Overlapping Instances Conformance Checking of Interacting Processes With Overlapping Instances Dirk Fahland, Massimiliano de Leoni, Boudewijn F. van Dongen, and Wil M.P. van der Aalst Eindhoven University of Technology, The

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

An Ontology-based Framework for Enriching Event-log Data

An Ontology-based Framework for Enriching Event-log Data An Ontology-based Framework for Enriching Event-log Data Thanh Tran Thi Kim, Hannes Werthner e-commerce group Institute of Software Technology and Interactive Systems, Vienna, Austria Email: kimthanh@ec.tuwien.ac.at,

More information

The Open University s repository of research publications and other research outputs

The Open University s repository of research publications and other research outputs Open Research Online The Open University s repository of research publications and other research outputs Semantic process mining tools: core building blocks Conference Item How to cite: de Medeiros, Ana

More information

Dept. of IT in Vel Tech Dr. RR & Dr. SR Technical University, INDIA. Dept. of Computer Science, Rashtriya Sanskrit Vidyapeetha, INDIA

Dept. of IT in Vel Tech Dr. RR & Dr. SR Technical University, INDIA. Dept. of Computer Science, Rashtriya Sanskrit Vidyapeetha, INDIA ISSN : 2229-4333(Print) ISSN : 0976-8491(Online) Analysis of Workflow and Process Mining in Dyeing Processing System 1 Saravanan. M.S, 2 Dr Rama Sree.R.J 1 Dept. of IT in Vel Tech Dr. RR & Dr. SR Technical

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

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

On Global Completeness of Event Logs

On Global Completeness of Event Logs On Global Completeness of Event Logs Hedong Yang 1, Arthur HM ter Hofstede 2,3, B.F. van Dongen 3, Moe T. Wynn 2, and Jianmin Wang 1 1 Tsinghua University, Beijing, China, 10084 yanghd06@mails.tsinghua.edu.cn,jimwang@tsinghua.edu.cn

More information

Genet A tool for the synthesis and mining of Petri nets. Josep Carmona jcarmonalsi.upc.edu Software Department Universitat Politcnica de Catalunya

Genet A tool for the synthesis and mining of Petri nets. Josep Carmona jcarmonalsi.upc.edu Software Department Universitat Politcnica de Catalunya Genet A tool for the synthesis and mining of Petri nets Josep Carmona jcarmonalsi.upc.edu Software Department Universitat Politcnica de Catalunya 2 Contents 1.1 Overview of the tool.......................

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

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

A Recommender System for Process Discovery

A Recommender System for Process Discovery A Recommender System for Process Discovery Joel Ribeiro 1, Josep Carmona 1, Mustafa Mısır 2, and Michele Sebag 2 1 Universitat Politècnica de Catalunya, Spain. {jribeiro, jcarmona}@lsi.upc.edu 2 TAO, INRIA

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

The Resultmaker Online Consultant: From Declarative Workflow Management in Practice to LTL

The Resultmaker Online Consultant: From Declarative Workflow Management in Practice to LTL The Resultmaker Online Consultant: From Declarative Workflow Management in Practice to LTL Mukkamala Raghava Rao Industrial PhD student IT University of Copenhagen & Resultmaker A/S rao@resultmaker.com

More information

From Workflow Design Patterns to Logical Specifications

From Workflow Design Patterns to Logical Specifications AUTOMATYKA/ AUTOMATICS 2013 Vol. 17 No. 1 http://dx.doi.org/10.7494/automat.2013.17.1.59 Rados³aw Klimek* From Workflow Design Patterns to Logical Specifications 1. Introduction Formal methods in software

More information

The Roman Model for Automated Synthesis in Practice: the SM4All Experience

The Roman Model for Automated Synthesis in Practice: the SM4All Experience The Roman Model for Automated Synthesis in Practice: the SM4All Experience An implementation of the game structure based automated syntesis of services applied to a real scenario Mario Caruso 1 Claudio

More information

Process Aware Host-based Intrusion Detection Model

Process Aware Host-based Intrusion Detection Model Process Aware Host-based Intrusion Detection Model Hanieh Jalali 1, Ahmad Baraani 1 1 University of Isfahan, Computer Department, Isfahan, Iran {jalali, ahmadb}@eng.ui.ac.ir 117 Abstract: Nowadays, many

More information

Managing and Tracing the Traversal of Process Clouds with Templates, Agendas and Artifacts

Managing and Tracing the Traversal of Process Clouds with Templates, Agendas and Artifacts Managing and Tracing the Traversal of Process Clouds with Templates, Agendas and Artifacts Marian Benner, Matthias Book, Tobias Brückmann, Volker Gruhn, Thomas Richter, Sema Seyhan paluno The Ruhr Institute

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

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

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

Designing and Evaluating an Interpretable Predictive Modeling Technique for Business Processes

Designing and Evaluating an Interpretable Predictive Modeling Technique for Business Processes Designing and Evaluating an Interpretable Predictive Modeling Technique for Business Processes Dominic Breuker 1, Patrick Delfmann 1, Martin Matzner 1 and Jörg Becker 1 1 Department for Information Systems,

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