Abstract
Service regulation applies modern management theory and information technology to provide intelligent, efficient and in-depth regulation of service quality and compliance operation. The Modern Service Industry with rapid innovation and evolution of services is confronted with many challenges such as compliance operation, yet traditional regulation methods rely heavily on manual labour and are less efficient. Therefore it is urgent to research efficient and intelligent methods of regulation in order to promote the healthy development of Modern Service Industry. As for process compliance in service regulation, this paper proposes a conceptual model of service regulation that includes service organization domain, business process domain and service regulation domain. Furthermore, a modeling language based on \(\pi \) calculus is introduced to formalize regulation issues. We have summarised six categories of general regulation rules based on regulation source materials from different service domains. To the best of our knowledge, there is currently no dataset available for service process violation recognition. Therefore, we construct a labelled process dataset for violation recognition (LPD4VR) of Internet healthcare service and propose a baseline method to detect the violation issue which achieves a recognition accuracy of 83.33%.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Van der Aalst, W., Adriansyah, A., van Dongen, B.: Replaying history on process models for conformance checking and performance analysis. Wiley Interdisc. Rev. Data Min. Knowl. Disc. 2(2), 182–192 (2012)
Alizadeh, M., Lu, X., Fahland, D., Zannone, N., van der Aalst, W.M.: Linking data and process perspectives for conformance analysis. Comput. Secur. 73, 172–193 (2018)
Augusto, A., Awad, A., Dumas, M.: Efficient checking of temporal compliance rules over business process event logs. arXiv preprint arXiv:2112.04623 (2021)
Berti, A., van der Aalst, W.M.P.: A novel token-based replay technique to speed up conformance checking and process enhancement. In: Koutny, M., Kordon, F., Pomello, L. (eds.) Transactions on Petri Nets and Other Models of Concurrency XV. LNCS, vol. 12530, pp. 1–26. Springer, Heidelberg (2021). https://doi.org/10.1007/978-3-662-63079-2_1
Burattin, A., van Zelst, S.J., Armas-Cervantes, A., van Dongen, B.F., Carmona, J.: online conformance checking using behavioural patterns. In: Weske, M., Montali, M., Weber, I., vom Brocke, J. (eds.) BPM 2018. LNCS, vol. 11080, pp. 250–267. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-98648-7_15
Dunzer, S., Stierle, M., Matzner, M., Baier, S.: Conformance checking: a state-of-the-art literature review. In: Proceedings of the 11th International Conference on Subject-Oriented Business Process Management, pp. 1–10 (2019)
Felli, P., Gianola, A., Montali, M., Rivkin, A., Winkler, S.: CoCoMoT: conformance checking of multi-perspective processes via SMT. In: Polyvyanyy, A., Wynn, M.T., Van Looy, A., Reichert, M. (eds.) BPM 2021. LNCS, vol. 12875, pp. 217–234. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-85469-0_15
Hashmi, M., Governatori, G., Lam, H.P., Wynn, M.T.: Are we done with business process compliance: state of the art and challenges ahead. Knowl. Inf. Syst. 57(1), 79–133 (2018)
de Leoni, M., van der Aalst, W.M.P., van Dongen, B.F.: Data- and resource-aware conformance checking of business processes. In: Abramowicz, W., Kriksciuniene, D., Sakalauskas, V. (eds.) BIS 2012. LNBIP, vol. 117, pp. 48–59. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-30359-3_5
Mannhardt, F., De Leoni, M., Reijers, H.A., Van Der Aalst, W.M.: Balanced multi-perspective checking of process conformance. Computing 98(4), 407–437 (2016)
Oliart, E., Rojas, E., Capurro, D.: Are we ready for conformance checking in healthcare? measuring adherence to clinical guidelines: a scoping systematic literature review. J. Biomed. Inf. 130, 104076 (2022)
Papazoglou, M.P.: Making business processes compliant to standards and regulations. In: 2011 IEEE 15th International Enterprise Distributed Object Computing Conference, pp. 3–13. IEEE (2011)
Parrow, J.: An introduction to the \(\pi \)-calculus. In: Handbook of Process algebra, pp. 479–543. Elsevier (2001)
Pegoraro, M., Uysal, M.S., van der Aalst, W.M.: Conformance checking over uncertain event data. Inf. Syst. 102, 101810 (2021)
Pufahl, L., Rehse, J.R.: Conformance checking with regulations-a research agenda. In: EMISA, pp. 24–29 (2021)
Siek, M., Mukti, R.: Business process mining from e-commerce event web logs: conformance checking and bottleneck identification. In: IOP Conference Series: Earth and Environmental Science, vol. 729, p. 012133. IOP Publishing (2021)
Valencia-Parra, Á., Varela-Vaca, Á.J., Gómez-López, M.T., Carmona, J., Bergenthum, R.: Empowering conformance checking using big data through horizontal decomposition. Inf. Syst. 99, 101731 (2021)
Wang, Y., Yu, W., Teng, P., Liu, G., Xiang, D.: A detection method for abnormal transactions in e-commerce based on extended data flow conformance checking. Wireless Commun. Mob. Comput. 2022 (2022)
Acknowledgements
This work was supported in part by National Natural Science Foundation of China under Grant 61825205, in part by the Key Research and Development Program of Zhejiang Provence under grant 2021C01017, in part by the Key Research Project of Zhejiang Province under Grant 2022C01145 and in part by the National Natural Science Foundation of China under Grants U20A20173 and 62125206.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Chen, J., Yin, J., Deng, S., Zhao, T., Xi, M. (2022). Service Regulation: Modeling and Recognition. In: Troya, J., Medjahed, B., Piattini, M., Yao, L., Fernández, P., Ruiz-Cortés, A. (eds) Service-Oriented Computing. ICSOC 2022. Lecture Notes in Computer Science, vol 13740. Springer, Cham. https://doi.org/10.1007/978-3-031-20984-0_6
Download citation
DOI: https://doi.org/10.1007/978-3-031-20984-0_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-20983-3
Online ISBN: 978-3-031-20984-0
eBook Packages: Computer ScienceComputer Science (R0)