Advertisement

MFI-5 Based Similarity Measurement of Business Process Models

  • Zhao Li
  • Jun Wu
  • Shuangmei Peng
  • Peng ChenEmail author
  • Jingsha He
  • Yiwang Huang
  • Keqing He
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11063)

Abstract

With the increasing use of business process model management techniques, a large number of business process models are being developed in the industry, so the corresponding enterprises and organizations usually need to maintain a large business process set. An approach is presented based on the Meta-model for process model registration (MFI-5) to accurately measure the similarity of process models. First, based on MFI-5, the Process Model Description Framework (PMDF) is constructed. According to PMDF, a similarity feature set of the process model (SFS) is defined. Second, the Business Process Modeling Notation (BPMN) is utilized to describe corresponding business process, and the BPMN models are obtained. Further the BPMN models are identified and quantified by using SFS, so the model vectors are obtained. At last, the Tanimoto Coefficient-based algorithm is utilized to calculate the similarity between any two vectors, the similarity measure matrix of the BPMN models can be extracted. We illustrate the approach in the context of measuring the similarity of the online sales service processes, the result of which shows that the proposed approach can facilitate business process recommendation.

Keywords

Business Process Model MFI-5 PMDF Similarity measure 

Notes

Acknowledgment

This work was supported by the National Key Research and Development Program of China (2016YFC0802500, 2016YFB0800403); the National Natural Science Foundation of China (61562073); the Humanities and Social Sciences Planning Fund of Ministry of Education (20171304); the Hubei Provincial Natural Science Foundation of China (2018CFC852); and the Natural Science Foundation of Hubei Provincial Department of Education (B2015240).

References

  1. 1.
    Wang, J., Yin, J., Dou, W.: Business process management technology preface. J. Softw. 26(3), 447–448 (2015)Google Scholar
  2. 2.
    Yan, Z., Dijkman, R.: Paul Grefen.: Fast business process similarity search. Distrib. Parallel Databases 30(2), 105–144 (2012)CrossRefGoogle Scholar
  3. 3.
    ISO/IEC-19763-5. Metamodel framework for interoperability (MFI)-part 5: metamodel for process model registration. https://www.iso.org/standard/53761.html. Accessed 15 May 2018
  4. 4.
    Comax, M., Chessa, S., Rieu, D., et al.: Evaluating the appropriateness of the BPMN 2.0 standard for modeling service choreographies: using an extended quality framework. Softw. Syst. Model. 15(1), 1–37 (2016)CrossRefGoogle Scholar
  5. 5.
    Cao, B., Wang, J., Fan, J., et al.: Mapping elements with the hungarian algorithm: an efficient method for querying business process models. In: International Conference on Web Services (ICWS), pp. 129–136. IEEE, New York (2015)Google Scholar
  6. 6.
    Akkiraju, R., Ivan, A.: Discovering business process similarities: an empirical study with SAP best practice business processes. In: Maglio, P.P., Weske, M., Yang, J., Fantinato, M. (eds.) ICSOC 2010. LNCS, vol. 6470, pp. 515–526. Springer, Heidelberg (2010).  https://doi.org/10.1007/978-3-642-17358-5_35CrossRefGoogle Scholar
  7. 7.
    Dijkman, R., Dumas, M., Van Dongen, B., et al.: Similarity of business process models: metrics and evaluation. Inf. Syst. 36(2), 498–516 (2011)CrossRefGoogle Scholar
  8. 8.
    Ehrig, M., Koschmider, A., Oberweis, A.: Measuring similarity between semantic business process models. In: International Conference on Conceptual Modeling, pp. 71–80. Springer, Heidelberg (2007)Google Scholar
  9. 9.
    Yan, Z., Dijkman, R., Grefen, P.: Fast business process similarity search with feature-based similarity estimation. In: Meersman, R., Dillon, T., Herrero, P. (eds.) OTM 2010. LNCS, vol. 6426, pp. 60–77. Springer, Heidelberg (2010).  https://doi.org/10.1007/978-3-642-16934-2_8CrossRefGoogle Scholar
  10. 10.
    Cao, B., Yin, J., Li, Y., et al.: A maximal common subgraph-based method for process retrieval. In: IEEE 20th International Conference on Web Services (ICWS), pp. 316–323. IEEE, New York (2013)Google Scholar
  11. 11.
    Huang, H., Peng, R., Feng, Z.: Efficient and exact query of large process model repositories in cloud workflow systems. IEEE Trans. Serv. Comput. (2015).  https://doi.org/10.1109/tsc.2015.2481409, https://ieeexplore.ieee.org/document/7274764/
  12. 12.
    Lu, Y., Yu, H., Ming, Z., Wang, H.: A similarity measurement based on structure of business process. In: IEEE 20th International Conference on Computer Supported Cooperative Work in Design (CSCWD), pp. 498–503. IEEE, New York (2016)Google Scholar
  13. 13.
    Zha, H., Wang, J., Wen, L., et al.: A workflow net similarity measure based on transition adjacency relations. Comput. Ind. 61(5), 463–471 (2010)CrossRefGoogle Scholar
  14. 14.
    Jin, T., Wang, J., Wen, L.: Querying business process models based on semantics. In: Yu, J.X., Kim, M.H., Unland, R. (eds.) DASFAA 2011. LNCS, vol. 6588, pp. 164–178. Springer, Heidelberg (2011).  https://doi.org/10.1007/978-3-642-20152-3_13CrossRefGoogle Scholar
  15. 15.
    Jin, T., Wang, J., Wen, L.: Efficient retrieval of similar workflow models based on behavior. In: Sheng, Quan Z., Wang, G., Jensen, Christian S., Xu, G. (eds.) APWeb 2012. LNCS, vol. 7235, pp. 677–684. Springer, Heidelberg (2012).  https://doi.org/10.1007/978-3-642-29253-8_64CrossRefGoogle Scholar
  16. 16.
    Grigori, D., Corrales, C., Bouzeghoub, M., et al.: Ranking BPEL processes for service discovery. IEEE Trans. Serv. Comput. 3(3), 178–192 (2010)CrossRefGoogle Scholar
  17. 17.
    Cheikhrouhou, S., Kallel, S., Jmaiel, M.: Toward a time-centric modeling of business processes models. In: IEEE 23rd International WETICE Conference, pp. 326–331. IEEE, New York (2014)Google Scholar
  18. 18.
    Geiger, M., Harrera, S., Lenhard, J., et al.: BPMN 2.0: the state of support and implementation. Future Gener. Comput. Syst. 80(3), 250–262 (2017)Google Scholar
  19. 19.
    Li, Z., Zhou, X., Keli, W., et al.: BPMN formalization based on extended petri nets model. Comput. Sci. 43(11), 40–48 (2016)Google Scholar
  20. 20.
    Syukriilah, N., Kusumo, D., Widowati, S.: Structural similarity analysis of business process model using selective reduce based on Petri Net. In: 3rd International Conference on Information and Communication Technology (ICoICT), pp. 1–5. IEEE, New York (2015)Google Scholar
  21. 21.
    Brocke, J., Rosemann, M.: Handbook on Business Process Management 1. 1st edn. Springer, Heidelberg (2010)Google Scholar
  22. 22.
    Xue, Z., Man, J., Zhang, C., et al.: Research on adaptability of BPMN based workflow execution process. Inf. Secur. Technol. 7(5), 56–58 (2016)Google Scholar
  23. 23.
    Qiao, M., Akkiraju, R., Rembert, A.J.: Towards efficient business process clustering and retrieval: combining language modeling and structure matching. In: Rinderle-Ma, S., Toumani, F., Wolf, K. (eds.) BPM 2011. LNCS, vol. 6896, pp. 199–214. Springer, Heidelberg (2011).  https://doi.org/10.1007/978-3-642-23059-2_17CrossRefGoogle Scholar
  24. 24.
    Appice, A., Malerba, D.: A co-training strategy for multiple view clustering in process mining. IEEE Trans. Serv. Comput. 9(6), 832–845 (2016)CrossRefGoogle Scholar
  25. 25.
    Kumar, A., Gupta, S., Singh, K., et al.: Comparison of various metrics used in collaborative filtering for recommendation system. In: 8th International Conference on Contemporary Computing (IC3), pp. 150–154. IEEE, New York (2015)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Zhao Li
    • 1
  • Jun Wu
    • 1
  • Shuangmei Peng
    • 1
  • Peng Chen
    • 1
    Email author
  • Jingsha He
    • 1
  • Yiwang Huang
    • 2
  • Keqing He
    • 3
  1. 1.College of Computer and Information TechnologyChina Three Gorges UniversityYichangChina
  2. 2.School of Data ScienceTongren UniversityTongrenChina
  3. 3.Computer SchoolWuhan UniversityWuhanChina

Personalised recommendations