Advertisement

Potentials of Image Mining for Business Process Management

  • Rainer Schmidt
  • Michael Möhring
  • Alfred Zimmermann
  • Ralf-Christian Härting
  • Barbara Keller
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 57)

Abstract

An enormous amount of data in the context of business processes is stored as images. They contain valuable information for business process management. Up to now this data had to be integrated manually into the business process. By advances of capturing it is possible to extract information from an increasing number of images. Therefore, we systematically investigate the potentials of Image Mining for business process management by a literature research and an in-depth analysis of the business process lifecycle. As a first step to evaluate our research, we developed a prototype for recovering process model information from drawings using Rapidminer.

Keywords

Image Mining BPM Business Process Management Object recognition Picture Process analysis 

References

  1. 1.
    Weske, M.: Business Process Management: Concepts, Languages, Architectures. Springer, Berlin, Heidelberg (2007)Google Scholar
  2. 2.
    Scheer, A.-W., Nüttgens, M.: ARIS architecture and reference models for business process management. In: van der Aalst, W., Desel, J., Oberweis, A. (eds.) Business Process Management, pp. 376–389. Springer, Berlin, Heidelberg (2000)CrossRefGoogle Scholar
  3. 3.
    White, S.A.: Introduction to BPMN. IBM Coop. 2008–029 (2004)Google Scholar
  4. 4.
    Bruno, G., Dengler, F., Jennings, B., Khalaf, R., Nurcan, S., Prilla, M., Sarini, M., Schmidt, R., Silva, R.: Key challenges for enabling agile BPM with social software. J. Softw. Maint. Evol. Res. Pract. 23, 297–326 (2011)CrossRefGoogle Scholar
  5. 5.
    Schmidt, R., Nurcan, S.: BPM and social software. In: Ardagna, D., Mecella, M., Yang, J., Aalst, W., Mylopoulos, J., Rosemann, M., Shaw, M.J., Szyperski, C. (eds.) Business Process Management Workshops, pp. 649–658. Springer, Berlin, Heidelberg (2009)CrossRefGoogle Scholar
  6. 6.
    Brynjolfsson, E.: Understanding the Digital Economy: Data, Tools, and Research: Data, Tools and Research. The MIT Press (2000)Google Scholar
  7. 7.
    Vincent, A., Varghese, G.: Towards A Robust and Stand-Alone System for Binarization and OCR of Document Images (2015)Google Scholar
  8. 8.
    Office Lens—Windows-Apps im Microsoft Store. https://www.microsoft.com/de-de/store/apps/office-lens/9wzdncrfj3t8
  9. 9.
    Team, O.: OneNote—what’s new in January 2016. https://blogs.office.com/2016/01/29/onenote-whats-new-in-january-2016/ (2016)
  10. 10.
    Zhang, J., Hsu, W., Lee, M.L.: Image mining: Issues, frameworks and techniques. In: Proceedings of the 2nd ACM SIGKDD International Workshop on Multimedia Data Mining (MDM/KDD’01). University of Alberta (2001)Google Scholar
  11. 11.
    Burl, M.C., Fowlkes, C., Roden, J.: Mining for image content. Syst. Cybern. Inf. Inf. Syst. Anal. Synth. (1999)Google Scholar
  12. 12.
    Mishra, N., Silakari, D.S.: Image mining in the context of content based image retrieval: a perspective. IJCSI Int. J. Comput. Sci. Issues 9, 98–107 (2012)Google Scholar
  13. 13.
    Stanchev, P., Flint, M.: Using image mining for image retrieval. In: IASTED Conference “Computer Science and Technology,” Cancun, Mexico, pp. 214–218 (2003)Google Scholar
  14. 14.
    Ordonez, C., Omiecinski, E.: Discovering association rules based on image content. In: IEEE Forum on Research and Technology Advances in Digital Libraries, 1999. Proceedings, pp. 38–49. IEEE (1999)Google Scholar
  15. 15.
    Carpenter, G., Grossberg, S., Markuzon, N., Reynolds, J.H., Rosen, A.B., et al.: Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps. IEEE Trans. Neural Netw. 3, 698–713 (1992)CrossRefGoogle Scholar
  16. 16.
    Kitchenham, B.: Procedures for performing systematic reviews. Keele UK Keele Univ. 33, 1–26 (2004)Google Scholar
  17. 17.
    Van der Aalst, W., ter Hofstede, A., Weske, M.: Business process management: a survey. Bus. Process. Manage. 1019–1019 (2003)Google Scholar
  18. 18.
    Dumas, M., La Rosa, M., Mendling, J., Reijers, H.A.: Fundamentals of Business Process Management. Springer, Berlin, Heidelberg (2013)CrossRefGoogle Scholar
  19. 19.
    Conger, S.: Six sigma and business process management. In: Handbook on Business Process Management, vol. 1, pp. 127–146. Springer (2015)Google Scholar
  20. 20.
    Wilson, P.F.: Root Cause Analysis: A Tool for Total Quality Management. ASQ Quality Press (1993)Google Scholar
  21. 21.
    Zhu, J.: Quantitative Models for Performance Evaluation and Benchmarking: Data Envelopment Analysis with Spreadsheets. Springer (2014)Google Scholar
  22. 22.
    Bach, V., Brecht, L., Hess, T., Österle, H.: Enabling Systematic Business Change: Integrated Methods and Software Tools for Business Process Redesign. Springer (2013)Google Scholar
  23. 23.
    Hajo, A.: Reijers: Implementing BPM systems: the role of process orientation. Bus. Process Manag. J. 12, 389–409 (2006)CrossRefGoogle Scholar
  24. 24.
    Metzger, A., Leitner, P., Ivanovic, D., Schmieders, E., Franklin, R., Carro, M., Dustdar, S., Pohl, K.: Comparing and combining predictive business process monitoring techniques. IEEE Trans. Syst. Man Cybern. Syst. 45, 276–290 (2015)CrossRefGoogle Scholar
  25. 25.
    Schmidt, R., Möhring, M., Härting, R.-C., Zimmermann, A., Heitmann, J., Blum, F.: Leveraging textual information for improving decision-making in the business process lifecycle. In: Neves-Silva, R., Jain, L.C., and Howlett, R.J. (eds.) Intelligent Decision Technologies. Sorrent (2015)Google Scholar
  26. 26.
    Naumann, J.D., Jenkins, A.M.: Prototyping: the new paradigm for systems development. Mis. Q. 29–44 (1982)CrossRefGoogle Scholar
  27. 27.
    Akthar, F., Hahne, C.: RapidMiner 5 Operator Reference. Rapid-GmbH (2012)Google Scholar
  28. 28.
    Burget, R., Karasek, J., Smékal, Z., Uher, V., Dostal, O.: Rapidminer image processing extension: a platform for collaborative research. In: Proceedings of the 33rd International Conference on Telecommunication and Signal Processing, pp. 114–118 (2010)Google Scholar
  29. 29.
    Masek, J., Burget, R., Karasek, J., Uher, V., Guney, S.: Evolutionary improved object detector for ultrasound images. In: 2013 36th International Conference on Telecommunications and Signal Processing (TSP), pp. 586–590. IEEE (2013)Google Scholar
  30. 30.
    Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2001. CVPR 2001, pp. I–511. IEEE (2001)Google Scholar
  31. 31.
    Tan, A.-H., et al.: Text mining: The state of the art and the challenges. In: Proceedings of the PAKDD 1999 Workshop on Knowledge Discovery from Advanced Databases, p. 65 (1999)Google Scholar
  32. 32.
    Van Der Aalst, W.: Process mining. Commun. ACM 55, 76–83 (2012)CrossRefGoogle Scholar
  33. 33.
    Wang, M., Wang, H.: From process logic to business logic—a cognitive approach to business process management. Inf. Manage. 43, 179–193 (2006)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 2.5 International License (http://creativecommons.org/licenses/by-nc/2.5/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

Authors and Affiliations

  • Rainer Schmidt
    • 1
  • Michael Möhring
    • 1
  • Alfred Zimmermann
    • 3
  • Ralf-Christian Härting
    • 2
  • Barbara Keller
    • 2
  1. 1.Munich University of Applied SciencesMunichGermany
  2. 2.Aalen University of Applied SciencesAalenGermany
  3. 3.Reutlingen UniversityReutlingenGermany

Personalised recommendations