Abstract
It is important to deal with rapidly changing environments (regulations, customer behavior change, and process improvement etc.) to keep achieving business goals. Therefore, verification for business process in various phases are needed to make sure of goal achievements. LTL (Linear Temporal Logic) verification is an important method for checking a specific property to be satisfied with business processes, but correctly writing formal language like LTL is difficult. Lacks of domain knowledge and knowledge of mathematical logics have bad influence on writing LTL formulas. In this paper, we use LTL verification and prediction based on decision tree learning for verification of specific properties. Furthermore, we helps writing properly LTL formula for representing the correct desirable property using decision tree constrction. We conducted a case study for evaluations.
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
Baeza-Yates, R.A.: Text retrieval: theory and practice. In: Proceedings of the 12th IFIP World Computer Congress 1992, pp. 465–476 (1992)
Cognini, R., Corradini, F., Gnesi, S., Polini, A., Re, B.: Research challenges in business process adaptability. In: Proceedings of the 29th Annual ACM Symposium on Applied Computing 2014, pp. 1049–1054. ACM (2014)
de Leoni, M., van der Aalst, W.M.P.: Aligning event logs and process models for multi-perspective conformance checking: An approach based on integer linear programming. In: Proceedings of 11th International Conference on Business Process Management 2013. LNCS, vol. 8094, pp. 113–129. Springer (2013)
de Medeiros, A.K.A., van der Aalst, W.M.P., Pedrinaci, C.: Semantic process mining tools: Core building blocks. In: Proceedings 16th European Conference on Information Systems 2008, pp. 1953–1964, AISeL (2008)
Hofstede, A., van der Aalst, W.M.P., Adams, M., Russell, N.: Modern Business Process Automation: YAWL and Its Support Environment, 1st edn. Springer, Berlin (2009)
Horita, H., Hirayama, H., Hayase, T., Tahara, Y., Ohsuga, A.: Goal achievement analysis based on LTL checking and decision tree for improvements of PAIS. In: Proceedings of 31th Annual ACM Symposium on Applied Computing 2016, pp. 1214–1216. ACM (2016)
Loh, W.Y.: Classification and regression trees. Data Min. Knowl. Disc. 1(1), 1423 (2011)
Maggi, F.M., Di Francescomarino, C., Dumas, M., Ghidini, C.: Predictive monitoring of business processes. In: Proceedings of 26th International Conference on Advanced Information Systems Engineering 2014. LNCS, vol. 8484, pp. 457–472. Springer (2014)
Mahleko, B., Wombacher, A.: Indexing business processes based on annotated finite state automata. In: Proceedings of International Conference on Web Services, pp. 303–311. IEEE Computer Society (2006)
Molka, T., Redlich, D., Drobek, M., Caetano, A., Zeng, X.J., Gilani, W.: Conformance checking for BPMN-Based process models. In: Proceedings of 29th Annual ACM Symposium on Applied Computing 2014, pp. 1406–1413. ACM (2014)
Montali, M., Maggi, F.M., Chesani, F., Mello, P., van der Aalst, W.M.P.: Monitoring business constraints with the event calculus. ACM Trans. Intell. Syst. Technol. 5(1), 17:1–17:30 (2014)
Pedregosa, et al.: Scikit-learn machine learning in python. J. Mach. Learn. Res. 12-2825-2830 (2011)
Pnueli, A.: The temporal logic of programs. In: Proceedings of the 18th Annual Symposium on Foundations of Computer Science 1977, pp. 46–57. IEEE Computer Society (1977)
Rozinat, A., van der Aalst, W.M.P.: Conformance checking of processes based on monitoring real behavior. Inf. Syst. 33(1), 64–95 (2008)
Shawe Taylor, J., Cristianini, N.: Kernel Methods for Pattern Analysis. 1st edn., Cambridge University Press (2004)
van der Aalst, W.M.P., de Beer, H.T., van Dongen B.F.: Process mining and verification of properties: an approach based on temporal logic. In: Proceedings of On the Move to Meaningful Internet Systems 2005: CoopIS, DOA, and ODBASE. LNCS, vol. 3760, pp. 130–147. Springer (2005)
van der Aalst, W.M.P.: Process Mining: Discovery, Conformance and Enhancement of Business Processes, 1st edn. Springer, Berlin (2011)
Wombacher, A.: Evaluation of technical measures for workflow similarity based on a pilot study. In: Proceedings of on the Move to Meaningful Internet Systems 2006: CoopIS, DOA, GADA, and ODBASE. LNCS, vol. 4275, pp. 255–272. Springer (2006)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Horita, H., Hirayama, H., Hayase, T., Tahara, Y., Ohsuga, A. (2016). Business Process Verification and Restructuring LTL Formula Based on Machine Learning Approach. In: Lee, R. (eds) Computer and Information Science. Studies in Computational Intelligence, vol 656. Springer, Cham. https://doi.org/10.1007/978-3-319-40171-3_7
Download citation
DOI: https://doi.org/10.1007/978-3-319-40171-3_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-40170-6
Online ISBN: 978-3-319-40171-3
eBook Packages: EngineeringEngineering (R0)