Process Discovery - Automated Approach for Block Discovery

Souhail Boushaba, Mohammed Issam Kabbaj, Zohra Bakkoury

2014

Abstract

Process mining is a set of techniques helping enterprises to avoid process modeling which is a time-consuming and error prone task. Process mining includes three topics: process discovery, conformance checking, and enhancement (IEEE Task Force on Process Mining: Process Mining Manifesto, 2012). The principle of process discovery is to extract information from event logs to capture the business process as it is being executed. Several techniques in literature (α algorithm, α+ algorithm and others) can be applied to discover a process model from a workflow log. However, as the amount of information grows exponentially, the log files (input of a process discovery algorithm) get bigger. In fact, classical techniques, which inspect relation between each couple of tasks will have problem dealing with big data. To this end, we introduced in (Boushaba et al., 2013) a new approach aiming to extract a block of tasks from event logs. In this paper, we present a new algorithm, based on a matrix representation, to detect a block of tasks. In addition, we develop an application to automate our technique.

References

  1. Agrawal, R., Gunopulos, D., and Leymann, F. 1998. Mining Process Models from Workflow Logs. Sixth International Conference on Extending Database Technology, pages 469-483.
  2. Van Der Aalst, W. M. P., Weijters, A. J. M. M., and Maruster L., 2004. Workflow Mining: Discovering Process Models from Event Logs. IEEE Transactions on Knowledge and Data Engineering, 16(9):1128- 1142.
  3. De Medeiros, A. K. A. ,Van Der Aalst, W. M. P., and Weijters, A. J. M. M. 2003.Workflow Mining: Current Status and Future Directions Department of Technology Management, Eindhoven University of Technology P.O. Box 513, NL-5600 MB, Eindhoven, The Netherlands, Springer,
  4. Weijters, A. J. M. M., Van Der Aalst, W. M. P., and De Medeiros, A. K. A., 2006. Process Mining with the Heuristics Miner Algorithm, BETA Working Paper Series, WP 166 Eindhoven University of Technology, Eindhoven.
  5. Boushaba, S., Kabbaj, M. I., Bakkoury, Z., 2013. Process mining: Matrix representation for bloc discovery, Intelligent Systems: Theories and Applications (SITA), IEEE.
  6. Murata, T., 1989. Petri Nets: Properties, Analysis and Applications, Apr. Proc. IEEE, vol. 77, no. 4, pp. 541- 580.
  7. De Medeiros, A. K. A., Weijters, A. J. M. M., and Van Der Aalst, W. M. P, 2004.Using Genetic Algorithms to Mine Process Models: Representation, Operators and Results, Eindhoven University of Technology, Eindhoven.
  8. Chen, Li., Manfred, R., and Wombacher, A., 2009. Discovering Reference Models by Mining Process Variants Using a Heuristic Approach.
  9. IEEE Task Force on Process Mining: Process Mining Manifesto, 2012. In: BPM Workshops. LNBIP, vol. 99, pp. 169-194. Springer
  10. Van der Aalst, W. M. P. 2011. Process Mining: Discovery, Conformance and Enhancement of Business Processes. Springer.
  11. Chen, Li., Manfred, R., Andreas, 2011, Mining Business Process Variants: Challenges, Scenarios, Algorithms, Data & Knowledge Engineering Elsevier,
  12. Wen L., Van der Aalst W. M. P., Wang J., and Sun J., 2007, Mining Process Models with Non-free- Choice Constructs. Data Mining and Knowledge Discovery, 15(2):145-180.
  13. Weijters, A. J. M. M. and van Der Aalst, W. M. P. 2003. Rediscovering Workflow Models from Event-Based Data Using Little Thumb. Integrated Computer-Aided Engineering, 10(2):151-162.
  14. Van der Aalst W. M. P., 2012. Desire Lines in Big Data, In proceeding of: Promoting Business Process Management Excellence in Russia (PropelleR 2012) 11-12.
  15. Leemans, S. J. J., Fahland, D., van der Aalst, W.M.P. 2013. Discovering block-structured process models from event logs -a constructive approach. In: Petri Nets. Lecture Notes in Computer Science, vol. 7927, pp. 311-329. Springer
  16. Leemans, Sander J. J., Fahland D. and van der Aalst W. M. P., 2013. Discovering Block-Structured Process Models from Event Logs Containing Infrequent Behaviour. fluxicon.com
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Paper Citation


in Harvard Style

Boushaba S., Issam Kabbaj M. and Bakkoury Z. (2014). Process Discovery - Automated Approach for Block Discovery . In Proceedings of the 9th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE, ISBN 978-989-758-030-7, pages 204-211. DOI: 10.5220/0004896402040211


in Bibtex Style

@conference{enase14,
author={Souhail Boushaba and Mohammed Issam Kabbaj and Zohra Bakkoury},
title={Process Discovery - Automated Approach for Block Discovery},
booktitle={Proceedings of the 9th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,},
year={2014},
pages={204-211},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004896402040211},
isbn={978-989-758-030-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,
TI - Process Discovery - Automated Approach for Block Discovery
SN - 978-989-758-030-7
AU - Boushaba S.
AU - Issam Kabbaj M.
AU - Bakkoury Z.
PY - 2014
SP - 204
EP - 211
DO - 10.5220/0004896402040211