research-article

Start time and duration distribution estimation in semi-structured processes

Authors:

Andreas Wombacher,

Maria-Eugenia lacobAuthors Info & Claims

SAC '13: Proceedings of the 28th Annual ACM Symposium on Applied Computing

Pages 1403 - 1409

https://doi.org/10.1145/2480362.2480626

Published: 18 March 2013 Publication History

Abstract

Semi-structured processes are business workflows, where the execution of the workflow is not completely controlled by a workflow engine, i.e., an implementation of a formal workflow model. Examples are workflows where actors potentially have interaction with customers reporting the result of the interaction in a process aware information system. Building a performance model for resource management in these processes is difficult since the required information is only partially recorded. In this paper we propose a systematic approach for the creation of an event log that is suitable for available process mining tools. This event log is created by an incrementally cleansing of data. The proposed approach is evaluated in an experiment.

References

[1]

M. Czerwinski, E. Horvitz, and S. Wilhite. A diary study of task switching and interruptions. In CHI, pages 175--182, 2004.

Digital Library

[2]

B. Dongen, A. Medeiros, H. M. W. Verbeek, A. J. M. M. Weijters, and W. Aalst. The proM framework: A new era in process mining tool support. In ICATPN, 2005.

Digital Library

[3]

K. Jensen. Coloured Petri Nets. Springer Verlag, Heidelberg, 1992.

[4]

K. Jensen, L. Kristensen, and L. Wells. Coloured petri nets and cpn tools for modelling and validation of concurrent systems. STTT, 9:213--254, 2007.

Digital Library

[5]

P. King. Computer and Communication Systems Performance Modelling. Prentice Hall, 1990.

Digital Library

[6]

C. Li, M. Reichert, and A. Wombacher. Discovering reference models by mining process variants using a heuristic approach. In BPM, pages 344--362. 2009.

Digital Library

[7]

G. Mark, V. M. González, and J. Harris. No task left behind?: examining the nature of fragmented work. In CHI, pages 321--330, 2005.

Digital Library

[8]

M. A. Marsan. Stochastic petri nets: an elementary introduction. In APN, pages 1--29, 1989.

Digital Library

[9]

A. Medeiros and C. W. Günther. Process mining: Using CPN tools to create test logs for mining algorithms. In Proc. of WS on the Practical Use of Coloured Petri Nets and CPN Tools (CPN), volume 576 of DAIMI, pages 177--190, 2005.

[10]

H. Motahari-Nezhad, R. Saint-Paul, F. Casati, and B. Benatallah. Event correlation for process discovery from web service interaction logs. The VLDB Journal, 20:417--444, 2011.

Digital Library

[11]

K. Musaraj, T. Yoshida, F. Daniel, M.-S. Hacid, F. Casati, and B. Benatallah. Message correlation and web service protocol mining from inaccurate logs. In ICWS, pages 259--266, 2010.

Digital Library

[12]

E. Parzen. On the estimation of a probability density function and mode. Annals of Mathematical Statistics, 33:1065--1076, 1962.

[13]

M. Rosenblatt. Remarks on some nonparametric estimates of a density function. The Annals of Mathematical Statistics, 1956:832--837, 1956.

[14]

A. Rozinat, R. S. Mans, M. Song, and W. Aalst. Discovering simulation models. Information Systems, 34(3):305--327, 2009.

Digital Library

[15]

A. Rozinat, R. S. Mans, M. Song, and W. M. P. van der Aalst. Discovering colored petri nets from event logs. STTT, 10(1):57--74, 2008.

Digital Library

[16]

Tou and Gonzalez. Pattern Recognition Principles. Addison-Wesley, Reading, 1974.

[17]

A. Wombacher and M.-E. Iacob. Estimating the processing time of process instances in semi-structured processes - a case study. In SCC, pages 368--375, 2012.

Digital Library

[18]

A. Wombacher, M.-E. Iacob, and M. Haitsma. Towards a performance estimate in semi-structured processes. In SOCA, pages 1--5, 2011.

Digital Library

Cited By

Depaire BMartin N(2022)Data-Driven Process SimulationEncyclopedia of Big Data Technologies10.1007/978-3-319-63962-8_102-2(1-9)Online publication date: 10-Mar-2022
https://doi.org/10.1007/978-3-319-63962-8_102-2
Shahzadi SFang XAlilah D(2021)Role of Stochastic Petri Net (SPN) in Process Discovery for Modelling and AnalysisMathematical Problems in Engineering10.1155/2021/86991642021(1-7)Online publication date: 30-Jun-2021
https://doi.org/10.1155/2021/8699164
Depaire BMartin N(2019)Data-Driven Process SimulationEncyclopedia of Big Data Technologies10.1007/978-3-319-77525-8_102(607-614)Online publication date: 20-Feb-2019
https://doi.org/10.1007/978-3-319-77525-8_102
Show More Cited By

Start time and duration distribution estimation in semi-structured processes
1. Computing methodologies
  1. Modeling and simulation
    1. Model development and analysis

Recommendations

Earliest Start Time Estimation for Advance Reservation-Based Resource Brokering within Computational Grids
ISPA '10: Proceedings of the International Symposium on Parallel and Distributed Processing with Applications

The ability to conduct advance reservations within grid environments is crucial for applications that want to utilize distributed resources in a predictable and efficient way. Advance reservations are essential for supporting deadline driven ...
Towards a performance estimate in semi-structured processes
SOCA '11: Proceedings of the 2011 IEEE International Conference on Service-Oriented Computing and Applications

Semi-structured processes are business workflows, where the execution of the workflow is not completely controlled by a workflow engine, i.e., an implementation of a formal workflow model. Examples are workflows where actors potentially have interaction ...
The GRID Computing Face with the Start of the LHC Experiments
ADVCOMP '08: Proceedings of the 2008 The Second International Conference on Advanced Engineering Computing and Applications in Sciences

The biggest particle accelerator in the world, the LHC, will begin to work by August 2008 and the four High Energy Experiments (ALICE, ATLAS, CMS and LHCb) hosted in the beam crossing caverns will start to take data. The amount of collected data will be ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

SAC '13: Proceedings of the 28th Annual ACM Symposium on Applied Computing

March 2013

2124 pages

ISBN:9781450316569

DOI:10.1145/2480362

Conference Chairs:
Sung Y. Shin
South Dakota State University, United States
,
José Carlos Maldonado
ICMC - University of São Paulo, Brazil

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGAPP: ACM Special Interest Group on Applied Computing

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 March 2013

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Qualifiers

Research-article

Conference

SAC '13

Sponsor:

SIGAPP

SAC '13: SAC '13

March 18 - 22, 2013

Coimbra, Portugal

Acceptance Rates

SAC '13 Paper Acceptance Rate 255 of 1,063 submissions, 24%;

Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

Upcoming Conference

SAC '25

Sponsor:
sigapp

The 40th ACM/SIGAPP Symposium on Applied Computing

March 31 - April 4, 2025

Catania , Italy

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

8
Total Citations
View Citations
106
Total Downloads

Downloads (Last 12 months)4
Downloads (Last 6 weeks)0

Reflects downloads up to 03 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Depaire BMartin N(2022)Data-Driven Process SimulationEncyclopedia of Big Data Technologies10.1007/978-3-319-63962-8_102-2(1-9)Online publication date: 10-Mar-2022
https://doi.org/10.1007/978-3-319-63962-8_102-2
Shahzadi SFang XAlilah D(2021)Role of Stochastic Petri Net (SPN) in Process Discovery for Modelling and AnalysisMathematical Problems in Engineering10.1155/2021/86991642021(1-7)Online publication date: 30-Jun-2021
https://doi.org/10.1155/2021/8699164
Depaire BMartin N(2019)Data-Driven Process SimulationEncyclopedia of Big Data Technologies10.1007/978-3-319-77525-8_102(607-614)Online publication date: 20-Feb-2019
https://doi.org/10.1007/978-3-319-77525-8_102
Milani FMaggi F(2018)A Comparative Evaluation of Log-Based Process Performance Analysis TechniquesBusiness Information Systems10.1007/978-3-319-93931-5_27(371-383)Online publication date: 16-Jun-2018
https://doi.org/10.1007/978-3-319-93931-5_27
Depaire BMartin N(2018)Data-Driven Process SimulationEncyclopedia of Big Data Technologies10.1007/978-3-319-63962-8_102-1(1-8)Online publication date: 5-Mar-2018
https://doi.org/10.1007/978-3-319-63962-8_102-1
Heinrich RMerkle PHenss JPaech B(2017)Integrating business process simulation and information system simulation for performance predictionSoftware and Systems Modeling (SoSyM)10.1007/s10270-015-0457-116:1(257-277)Online publication date: 1-Feb-2017
https://dl.acm.org/doi/10.1007/s10270-015-0457-1
Martin NDepaire BCaris A(2015)The Use of Process Mining in Business Process Simulation Model ConstructionBusiness & Information Systems Engineering10.1007/s12599-015-0410-458:1(73-87)Online publication date: 3-Nov-2015
https://doi.org/10.1007/s12599-015-0410-4
Rogge-Solti Avan der Aalst WWeske M(2014)Discovering Stochastic Petri Nets with Arbitrary Delay Distributions from Event LogsBusiness Process Management Workshops10.1007/978-3-319-06257-0_2(15-27)Online publication date: 10-May-2014
https://doi.org/10.1007/978-3-319-06257-0_2

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents