Skip to main content

Process Mining: On the Fly Process Discovery

  • Conference paper
  • First Online:
  • 868 Accesses

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 381))

Abstract

Process mining is a set of techniques helping enterprises to avoid process modeling, which is time consuming, and error prone task. The goal of such techniques is to extract the process as it has been executed. However, the increase of data production in event logs of process aware information systems makes it necessary to mine the processes in real time. For this purpose, it is necessary to define new approaches for process discovery analyzing data on the fly. This paper presents a new process discovery approach aiming to extract data on the fly by discovering the set of blocks composing the process.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. van der Aalst, W.M.P., Weijters, A.J.M.M., Maruster, L.: Workflow mining: discovering process models from event logs. IEEE Trans. Knowl. Data Eng. 16(9), 1128–1142 (2004) (IEEE Transactions)

    Google Scholar 

  2. Boushaba, S., Kabbaj, M.I., Bakkoury, Z.: Process discovery: automated approach block discovery, evavluation of novel approaches in software engineering (ENASE) 2013

    Google Scholar 

  3. De Medeiros, A.K.A., Weijters, A.J.M.M., Van Der Aalst, W.M.P.: Using Genetic Algorithms to Mine Process Models: Representation, Operators and Results. Eindhoven University of Technology, Eindhoven (2004)

    Google Scholar 

  4. Weijters, A.J.M.M., Ribeiro, J.T.S.: Flexible Heuristics Miner (FHM). BETA Working Paper Series, WP 334, Eindhoven University of Technology, Eindhoven (2010)

    Google Scholar 

  5. Wen, L., van der Aalst, W.M.P., Wang, J., Sun, J.: Mining process models with non-free-choice constructs. Data Min. Knowl. Disc. 15, 145–180 (2007)

    Google Scholar 

  6. Boushaba, S., Kabbaj, M.I., Bakkoury, Z.: Process mining: matrix representation for block discovery. In: Intelligent Systems: Theories and Applications (SITA), IEEE (2013)

    Google Scholar 

  7. IEEE Task Force on Process Mining: Process Mining Manifesto. In: BPM Workshops. LNBIP, vol. 99, pp. 169–194. Springer (2012)

    Google Scholar 

  8. Burattin, A., Sperduti, A., van der Aalst, W.M.P.: Control-flow Discovery from Event Streams IEEE Congress on Evolutionary Computation, IEEE (2014)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Souhail Boushaba .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Boushaba, S., Kabbaj, M.I., Bakkoury, Z., Matais, S.M. (2016). Process Mining: On the Fly Process Discovery. In: El Oualkadi, A., Choubani, F., El Moussati, A. (eds) Proceedings of the Mediterranean Conference on Information & Communication Technologies 2015. Lecture Notes in Electrical Engineering, vol 381. Springer, Cham. https://doi.org/10.1007/978-3-319-30298-0_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-30298-0_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-30296-6

  • Online ISBN: 978-3-319-30298-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics