Abstract
Textual process descriptions are widely used in organizations since they can be created and understood by virtually everyone. The inherent ambiguity of natural language, however, impedes the automated analysis of textual process descriptions. While human readers can use their context knowledge to correctly understand statements with multiple possible interpretations, automated analysis techniques currently have to make assumptions about the correct meaning. As a result, automated analysis techniques are prone to draw incorrect conclusions about the correct execution of a process. To overcome this issue, we introduce the concept of a behavioral space as a means to deal with behavioral ambiguity in textual process descriptions. A behavioral space captures all possible interpretations of a textual process description in a systematic manner. Thus, it avoids the problem of focusing on a single interpretation. We use a compliance checking scenario and a quantitative evaluation with a set of 47 textual process descriptions to demonstrate the usefulness of a behavioral space for reasoning about a process described by a text. Our evaluation demonstrates that a behavioral space strikes a balance between ignoring ambiguous statements and imposing fixed interpretations on them.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
- 2.
For processes that contain loops, we only include traces with at most one repetition.
References
Van der Aa, H., Leopold, H., Mannhardt, F., Reijers, H.A.: On the fragmentation of process information: challenges, solutions, and outlook. In: Gaaloul, K., Schmidt, R., Nurcan, S., Guerreiro, S., Ma, Q. (eds.) BPMDS 2015 and EMMSAD 2015. LNBIP, vol. 214, pp. 3–18. Springer, Heidelberg (2015)
Van der Aa, H., Leopold, H., Reijers, H.A.: Detecting inconsistencies between process models and textual descriptions. In: Motahari-Nezhad, H.R., Recker, J., Weidlich, M. (eds.) BPM 2015. LNCS, vol. 9253, pp. 90–105. Springer, Heidelberg (2015)
Abiteboul, S., Kanellakis, P., Grahne, G.: On the representation and querying of sets of possible worlds, vol. 16. ACM (1987)
Aggarwal, C.C., Yu, P.S.: A survey of uncertain data algorithms and applications. IEEE Trans. Knowl. Data Eng. 21(5), 609–623 (2009)
Dijkman, R., Dumas, M., GarcÃa-Bañuelos, L.: Graph matching algorithms for business process model similarity search. In: Dayal, U., Eder, J., Koehler, J., Reijers, H.A. (eds.) BPM 2009. LNCS, vol. 5701, pp. 48–63. Springer, Heidelberg (2009)
Friedrich, F., Mendling, J., Puhlmann, F.: Process model generation from natural language text. In: Mouratidis, H., Rolland, C. (eds.) CAiSE 2011. LNCS, vol. 6741, pp. 482–496. Springer, Heidelberg (2011)
Ghose, A., Koliadis, G., Chueng, A.: Process discovery from model and text artefacts. In: 2007 IEEE Congress on Services, pp. 167–174. IEEE (2007)
de AR Gonçalves, J.C., Santoro, F.M., Baiao, F.A.: Business process mining from group stories. In: 13th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2009, pp. 161–166. IEEE (2009)
Imieliński, T., Lipski Jr., W.: Incomplete information in relational databases. J. ACM (JACM) 31(4), 761–791 (1984)
Leopold, H., Mendling, J., Polyvyanyy, A.: Supporting process model validation through natural language generation. IEEE Trans. Software Eng. 40(8), 818–840 (2014)
Leopold, H., Pittke, F., Mendling, J.: Automatic service derivation from business process model repositories via semantic technology. J. Syst. Softw. 108, 134–147 (2015)
Liu, Y., Muller, S., Xu, K.: A static compliance-checking framework for business process models. IBM Syst. J. 46(2), 335–361 (2007)
Pei, J., Jiang, B., Lin, X., Yuan, Y.: Probabilistic skylines on uncertain data. In: Proceedings of the 33rd International Conference on Very Large Data Bases, pp. 15–26 (2007)
Peng, L., Diao, Y.: Supporting data uncertainty in array databases. In: ACM SIGMOD International Conference on Management of Data, pp. 545–560. ACM (2015)
Pittke, F., Leopold, H., Mendling, J.: When language meets language: anti patterns resulting from mixing natural and modeling language. In: Fournier, F., Mendling, J. (eds.) BPM 2014 Workshops. LNBIP, vol. 202, pp. 118–129. Springer, Heidelberg (2015)
Riefer, M., Ternis, S.F., Thaler, T.: Mining process models from natural language text: a state-of-the-art analysis. In: Multikonferenz Wirtschaftsinformatik (MKWI-16), March 9–11, Illmenau, Germany. Universität Illmenau (2016)
Sarma, A.D., Benjelloun, O., Halevy, A., Widom, J.: Working models for uncertain data. In: 22nd International Conference on Data Engineering, p. 7. IEEE (2006)
Selway, M., Grossmann, G., Mayer, W., Stumptner, M.: Formalising natural language specifications using a cognitive linguistic/configuration based approach. Inf. Syst. 54, 191–208 (2015)
Sinha, A., Paradkar, A.: Use cases to process specifications in Business Process Modeling Notation. In: IEEE International Conference on Web Services, pp. 473–480 (2010)
Smirnov, S., Weidlich, M., Mendling, J.: Business process model abstraction based on behavioral profiles. In: Weske, M., Yang, J., Fantinato, M., Maglio, P.P. (eds.) ICSOC 2010. LNCS, vol. 6470, pp. 1–16. Springer, Heidelberg (2010)
Viorica Epure, E., Martin-Rodilla, P., Hug, C., Deneckere, R., Salinesi, C.: Automatic process model discovery from textual methodologies. In: 2015 IEEE 9th International Conference on Research Challenges in Information Science (RCIS), pp. 19–30. IEEE (2015)
Weidlich, M., Mendling, J., Weske, M.: Efficient consistency measurement based on behavioral profiles of process models. IEEE Trans. Software Eng. 37(3), 410–429 (2011)
Weidlich, M., Polyvyanyy, A., Desai, N., Mendling, J., Weske, M.: Process compliance analysis based on behavioural profiles. Inf. Syst. 36(7), 1009–1025 (2011)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
van der Aa, H., Leopold, H., Reijers, H.A. (2016). Dealing with Behavioral Ambiguity in Textual Process Descriptions. In: La Rosa, M., Loos, P., Pastor, O. (eds) Business Process Management. BPM 2016. Lecture Notes in Computer Science(), vol 9850. Springer, Cham. https://doi.org/10.1007/978-3-319-45348-4_16
Download citation
DOI: https://doi.org/10.1007/978-3-319-45348-4_16
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-45347-7
Online ISBN: 978-3-319-45348-4
eBook Packages: Computer ScienceComputer Science (R0)