Abstract
Business process management has become an increasingly present activity in organizations. In this context, approaches that assist in the identification and documentation of business processes are presented as relevant efforts to make organizations more competitive. To achieve these goals, business process descriptions are considered as a useful artifact in both identifying business processes and complementing business process documentation. However, approaches that automatically generate business process descriptions do not explain how the sentence templates that compose the text were selected. This selection influences the quality of the text, as it may produce ambiguous or non-recurring sentences, which could make it difficult to understand the process. In this work, we present an empirical analysis of 64 business process descriptions in order to find recurrent sentence templates and filter them for ambiguity issues. The analysis made it possible to find 101 sentence templates divided into 29 categories. In addition, 13 of the sentence templates were considered to have ambiguity issues based on the adopted criteria. These findings may support other approaches in generating process descriptions more suitable for process analysts and domain experts.
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References
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, Cham (2015). https://doi.org/10.1007/978-3-319-23063-4_6
van der Aa, H., Leopold, H., Reijers, H.A.: Dealing with behavioral ambiguity in textual process descriptions. In: La Rosa, M., Loos, P., Pastor, O. (eds.) BPM 2016. LNCS, vol. 9850, pp. 271–288. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-45348-4_16
van der Aa, H., Leopold, H., Reijers, H.A.: Checking process compliance against natural language specifications using behavioral spaces. Inf. Syst. (2018)
Akbar, S., Bajwa, I.S., Malik, S.: Scope resolution of logical connectives in NL constraints. In: Eighth International Conference on Digital Information Management, pp. 217–222. IEEE (2013)
de AR Goncalves, 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)
de AR Gonçalves, J.C., Santoro, F.M., Baião, F.A.: Let me tell you a story-on how to build process models. J. UCS 17(2), 276–295 (2011)
Aysolmaz, B., Leopold, H., Reijers, H.A., Demirörs, O.: A semi-automated approach for generating natural language requirements documents based on business process models. Inf. Softw. Technol. 93, 14–29 (2018)
Caporale, T.: A tool for natural language oriented business process modeling. In: ZEUS, pp. 49–52 (2016)
Dumas, M., La Rosa, M., Mendling, J., Reijers, H.A., et al.: Fundamentals of Business Process Management, vol. 1. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-33143-5
Epure, E.V., Martín-Rodilla, P., Hug, C., Deneckère, 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)
Ferrari, A., Witschel, H.F., Spagnolo, G.O., Gnesi, S.: Improving the quality of business process descriptions of public administrations: resources and research challenges. Bus. Process Manag. J. 24, 49–66 (2017)
Ferreira, R.C.B., Thom, L.H., de Oliveira, J.P.M., Avila, D.T., dos Santos, R.I., Fantinato, M.: Assisting process modeling by identifying business process elements in natural language texts. In: de Cesare, S., Frank, U. (eds.) ER 2017. LNCS, vol. 10651, pp. 154–163. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-70625-2_15
Friedrich, F.: Automated generation of business process models from natural language input. M.Sc., School of Business and Economics. Humboldt-Universität zu Berli (2010)
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). https://doi.org/10.1007/978-3-642-21640-4_36
Ghose, A., Koliadis, G., Chueng, A.: Process discovery from model and text artefacts. In: 2007 IEEE Congress on Services, pp. 167–174. IEEE (2007)
Leopold, H., van der Aa, H., Pittke, F., Raffel, M., Mendling, J., Reijers, H.A.: Integrating textual and model-based process descriptions for comprehensive process search. In: Schmidt, R., Guédria, W., Bider, I., Guerreiro, S. (eds.) BPMDS/EMMSAD -2016. LNBIP, vol. 248, pp. 51–65. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-39429-9_4
Leopold, H., Mendling, J., Polyvyanyy, A.: Generating natural language texts from business process models. In: Ralyté, J., Franch, X., Brinkkemper, S., Wrycza, S. (eds.) CAiSE 2012. LNCS, vol. 7328, pp. 64–79. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-31095-9_5
Leopold, H., Mendling, J., Polyvyanyy, A.: Supporting process model validation through natural language generation. IEEE Trans. Softw. Eng. 40(8), 818–840 (2014)
Li, J., Wang, H.J., Zhang, Z., Zhao, J.L.: A policy-based process mining framework: mining business policy texts for discovering process models. Inf. Syst. E-Bus. Manag. 8(2), 169–188 (2010)
Meitz, M., Leopold, H., Mendling, J.: An approach to support process model validation based on text generation. In: EMISA Forum, vol. 33, pp. 7–20 (2013)
Nawrocki, J.R., Nedza, T., Ochodek, M., Olek, L.: Describing business processes with use cases. In: BIS, pp. 13–27 (2006)
OMG: Business process modeling notation (BPMN) version 2.0.2 (2013). https://www.omg.org/spec/BPMN/
Ottensooser, A., Fekete, A., Reijers, H.A., Mendling, J., Menictas, C.: Making sense of business process descriptions: an experimental comparison of graphical and textual notations. J. Syst. Softw. 85(3), 596–606 (2012)
Sànchez-Ferreres, J., Carmona, J., Padró, L.: Aligning textual and graphical descriptions of processes through ILP techniques. In: Dubois, E., Pohl, K. (eds.) CAiSE 2017. LNCS, vol. 10253, pp. 413–427. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-59536-8_26
Sinha, A., Paradkar, A.: Use cases to process specifications in business process modeling notation. In: 2010 IEEE International Conference on Web Services (ICWS), pp. 473–480. IEEE (2010)
Acknowledgments
We are grateful to the national research funding agencies CNPq (National Council for Scientific and Technological Development) and CAPES (CAPES Foundation) for financial support. We also acknowledge the support we have been receiving from the Graduate Program in Computer Science as well as the Institute of Informatics, UFRGS.
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Silva, T.S., Thom, L.H., Weber, A., de Oliveira, J.P.M., Fantinato, M. (2018). Empirical Analysis of Sentence Templates and Ambiguity Issues for Business Process Descriptions. In: Panetto, H., Debruyne, C., Proper, H., Ardagna, C., Roman, D., Meersman, R. (eds) On the Move to Meaningful Internet Systems. OTM 2018 Conferences. OTM 2018. Lecture Notes in Computer Science(), vol 11229. Springer, Cham. https://doi.org/10.1007/978-3-030-02610-3_16
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