Research article Special Issues

Reconstructing invisible deviating events: A conformance checking approach for recurring events

  • Received: 25 April 2022 Revised: 11 July 2022 Accepted: 15 July 2022 Published: 16 August 2022
  • Conformance checking enables organizations to determine whether their executed processes are compliant with the intended process. However, if the processes contain recurring activities, state-of-the-art approaches unfortunately have difficulties calculating the conformance. The occurrence of complex temporal rules can further increase the complexity of the problem. Identifying this limitation, this paper presents a novel approach towards dealing with recurring activities in conformance checking. The core idea of the approach is to reconstruct the missing events in the event log using defined rules while incorporating specified temporal event characteristics. This approach then enables the use of native conformance checking algorithms. The paper illustrates the algorithmic approach and defines the required temporal event characteristics. Furthermore, the approach is applied and evaluated in a case study on an event log for melanoma surveillance.

    Citation: Joscha Grüger, Martin Kuhn, Ralph Bergmann. Reconstructing invisible deviating events: A conformance checking approach for recurring events[J]. Mathematical Biosciences and Engineering, 2022, 19(11): 11782-11799. doi: 10.3934/mbe.2022549

    Related Papers:

  • Conformance checking enables organizations to determine whether their executed processes are compliant with the intended process. However, if the processes contain recurring activities, state-of-the-art approaches unfortunately have difficulties calculating the conformance. The occurrence of complex temporal rules can further increase the complexity of the problem. Identifying this limitation, this paper presents a novel approach towards dealing with recurring activities in conformance checking. The core idea of the approach is to reconstruct the missing events in the event log using defined rules while incorporating specified temporal event characteristics. This approach then enables the use of native conformance checking algorithms. The paper illustrates the algorithmic approach and defines the required temporal event characteristics. Furthermore, the approach is applied and evaluated in a case study on an event log for melanoma surveillance.



    加载中


    [1] J. Wang, S. Song, X. Zhu, X. Lin, Efficient recovery of missing events, Proceed. VLDB Endowment., 6 (2013), 841–852. https://doi.org/10.14778/2536206.2536212 doi: 10.14778/2536206.2536212
    [2] W. Van der Aalst, T. Weijters, L. Maruster, Workflow mining: Discovering process models from event logs, IEEE Transact. Knowl. Data Eng., 16 (2004), 1128–1142. https://doi.org/10.1109/TKDE.2004.47 doi: 10.1109/TKDE.2004.47
    [3] F. Mannhardt, Multi-perspective process mining, PhD thesis, Technische Universiteit Eindhoven, 2018.
    [4] A. Burattin, F. Maggi, A. Sperduti, Conformance checking based on multi-perspective declarative process models, Expert Syst. Appl., 65 (2016), 194–211. https://doi.org/10.1016/j.eswa.2016.08.040 doi: 10.1016/j.eswa.2016.08.040
    [5] S. Zhang, L. Genga, H. Yan, H. Nie, X. Lu, U. Kaymak, Towards multi-perspective conformance checking with fuzzy sets, Int. J. Interact. Mult. Artif. Intell., 6 (2020), 134. https://doi.org/10.9781/ijimai.2021.02.013 doi: 10.9781/ijimai.2021.02.013
    [6] C. Rinner, E. Helm, R. Dunkl, H. Kittler, S. Rinderle-Ma, An application of process mining in the context of melanoma surveillance using time boxing, in Business Process Management Workshops. BPM 2018. Lecture Notes in Business Information Processing (eds. F. Daniel, Q. Sheng and H. Motahari), vol. 342, Springer, 2019,175–186. https://doi.org/10.1007/978-3-030-11641-5_14
    [7] M. Eck, X. Lu, S. Leemans, W. Aalst, PM$^2$: A process mining project methodology, Adv. Inform. Syst. Eng., (2015), 297–313. https://doi.org/10.1007/978-3-319-19069-3_19 doi: 10.1007/978-3-319-19069-3_19
    [8] W. M. P. van der Aalst, A. Adriansyah, A. K. A. de Medeiros, F. Arcieri, T. Baier, T. Blickle, et al., Process mining manifesto, in Business Process Management Workshops (eds. F. Daniel, K. Barkaoui and S. Dustdar), vol. 99 of Lecture Notes in Business Information Processing, Springer Berlin Heidelberg, Berlin, Heidelberg, 2012,169–194. https://doi.org/10.1007/978-3-642-28108-2_19
    [9] S. J. van Zelst, F. Mannhardt, M. de Leoni, A. Koschmider, Event abstraction in process mining: Literature review and taxonomy, Granular Comput., 6 (2020), 719–736. https://doi.org/10.1007/s41066-020-00226-2 doi: 10.1007/s41066-020-00226-2
    [10] W. M. P. van der Aalst, Data Science in Action, 2nd edition, Springer Berlin Heidelberg, 2016. https://doi.org/10.1007/978-3-662-49851-4_1
    [11] M. Rovani, F. M. Maggi, M. de Leoni, W. M. P. van der Aalst, Declarative process mining in healthcare, Expert Syst. Appl., 42 (2015), 9236–9251. https://doi.org/10.1016/j.eswa.2015.07.040 doi: 10.1016/j.eswa.2015.07.040
    [12] A. Adriansyah, Aligning observed and modeled behavior, PhD thesis, Technische Universiteit Eindhoven, 2014.
    [13] A. Adriansyah, J. Munoz-Gama, J. Carmona, B. F. van Dongen, W. M. P. van der Aalst, Alignment based precision checking, in Business Process Management Workshops (eds. M. La Rosa and P. Soffer), vol. 132, Springer Berlin Heidelberg, 2013,137–149. https://doi.org/10.1007/978-3-642-36285-9_15
    [14] M. de Leoni, W. M. P. van der Aalst, Aligning event logs and process models for multi-perspective conformance checking: An approach based on integer linear programming, in Business process management (eds. F. Daniel, J. Wang and B. Weber), vol. 8094 of LNCS sublibrary: SL 3 - Information systems and application, incl. Internet/Web and HCI, Springer, Heidelberg, 2013,113–129. https://doi.org/10.1007/978-3-642-40176-3_10
    [15] S. Dunzer, M. Stierle, M. Matzner, S. Baier, Conformance checking: A state-of-the-art literature review, in Proceedings of the 11th International Conference on Subject-Oriented Business Process Management (ed. S. Betz), Association for Computing Machinery, New York, 2019, 1–10. https://doi.org/10.1145/3329007.3329014
    [16] A. Alharbi, A. Bulpitt, O. Johnson, Improving pattern detection in healthcare process mining using an interval-based event selection method, in Business Process Management Forum (eds. J. Carmona, G. Engels and A. Kumar), Springer International Publishing, 2017, 88–105. https://doi.org/10.1007/978-3-319-65015-9_6
    [17] C. Garbe, K. Peris, A. Hauschild, P. Saiag, M. Middleton, L. Bastholt, et al., Diagnosis and treatment of melanoma: European consensus-based interdisciplinary guideline, Eur. J. Cancer, 46 (2010), 270–283. https://doi.org/10.1016/j.ejca.2009.10.032 doi: 10.1016/j.ejca.2009.10.032
    [18] C. Duan, Q. Wei, Process mining of duplicate tasks: A systematic literature review, in 2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA), (2020), 778–784. https://doi.org/10.1109/ICAICA50127.2020.9182667
    [19] R. J. C. Bose, R. S. Mans, W. M. P. van der Aalst, Wanna improve process mining results?, in 2013 IEEE Symposium on Computational Intelligence and Data Mining (CIDM), (2013), 127–134.
    [20] S. K. Vanden Broucke, F. Caron, J. Lismont, J. Vanthienen, B. Baesens, On the gap between reality and registration: A business event analysis classification framework, 17 (2016), 393–-410. https://doi.org/10.1007/s10799-016-0262-8
    [21] J. Swinnen, K. Vanhoof, E. Hannes, Querying event logs: Discovering non-events in event logs, 2010 IEEE International Conference On Intelligent Systems And Knowledge Engineering, (2010), 349–354. https://doi.org/10.1109/ISKE.2010.5680850 doi: 10.1109/ISKE.2010.5680850
    [22] C. Balch, J. Gershenwald, S.-J. Soong, J. Thompson, M. Atkins, D. Byrd, et al., Final version of 2009 ajcc melanoma staging and classification, J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol., 27 (2009), 6199–206. https://doi.org/10.1200/JCO.2009.23.4799 doi: 10.1200/JCO.2009.23.4799
  • Reader Comments
  • © 2022 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(446) PDF downloads(33) Cited by(0)

Article outline

Figures and Tables

Figures(6)  /  Tables(5)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog