Abstract
Process models are an important means to capture information on organizational operations and often represent the starting point for process analysis and improvement. Since the manual elicitation and creation of process models is a time-intensive endeavor, a variety of techniques have been developed that automatically derive process models from textual process descriptions. However, these techniques, so far, only focus on the extraction of traditional, imperative process models. The extraction of declarative process models, which allow to effectively capture complex process behavior in a compact fashion, has not been addressed. In this paper we close this gap by presenting the first automated approach for the extraction of declarative process models from natural language. To achieve this, we developed tailored Natural Language Processing techniques that identify activities and their inter-relations from textual constraint descriptions. A quantitative evaluation shows that our approach is able to generate constraints that closely resemble those established by humans. Therefore, our approach provides automated support for an otherwise tedious and complex manual endeavor.
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References
Van der Aa, H., Leopold, H., Reijers, H.A.: Comparing textual descriptions to process models: the automatic detection of inconsistencies. Inf. Syst. 64, 447–460 (2017)
Van der Aa, H., Leopold, H., Reijers, H.A.: Checking process compliance against natural language specifications using behavioral spaces. Inf. Syst. 78, 83–95 (2018)
Van der Aa, H., Leopold, H., van de Weerd, I., Reijers, H.A.: Causes and consequences of fragmented process information: insights from a case study. In: 23rd Americas Conference on Information Systems, AMCIS (2017)
Van der Aalst, W.M.P., Pesic, M., Schonenberg, H.: Declarative workflows: balancing between flexibility and support. Comput. Sci. R&D 23(2), 99–113 (2009)
Androutsopoulos, I.: Exploring Time, Tense and Aspect in Natural Language Database Interfaces, vol. 6. John Benjamins Publishing, Amsterdam (2002)
Baier, T., Mendling, J.: Bridging abstraction layers in process mining by automated matching of events and activities. In: Daniel, F., Wang, J., Weber, B. (eds.) BPM 2013. LNCS, vol. 8094, pp. 17–32. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-40176-3_4
De Marneffe, M.C., Manning, C.D.: The Stanford typed dependencies representation. In: Workshop on Cross-Framework and Cross-Domain Parser Evaluation, pp. 1–8 (2008)
Di Ciccio, C., Maggi, F.M., Mendling, J.: Efficient discovery of target-branched declare constraints. Inf. Syst. 56, 258–283 (2016)
Di Ciccio, C., Maggi, F.M., Montali, M., Mendling, J.: Resolving inconsistencies and redundancies in declarative process models. Inf. Syst. 64, 425–446 (2017)
Di Ciccio, C., Marrella, A., Russo, A.: Knowledge-intensive processes: characteristics, requirements and analysis of contemporary approaches. J. Data Semant. 4(1), 29–57 (2015)
Di Ciccio, C., Mecella, M.: On the discovery of declarative control flows for artful processes. ACM Trans. Manag. Inf. Syst. 5(4), 24:1–24:37 (2015)
Dragoni, M., Villata, S., Rizzi, W., Governatori, G.: Combining natural language processing approaches for rule extraction from legal documents. In: Pagallo, U., Palmirani, M., Casanovas, P., Sartor, G., Villata, S. (eds.) AICOL 2015-2017. LNCS (LNAI), vol. 10791, pp. 287–300. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-00178-0_19
Dumas, M., La Rosa, M., Mendling, J., Reijers, H.A.: Fundamentals of BusinessProcess Management, 2nd edn. Springer, Heidelberg (2018). https://doi.org/10.1007/978-3-662-56509-4
Dwyer, M.B., Avrunin, G.S., Corbett, J.C.: Patterns in property specifications for finite-state verification. In: ICSE, pp. 411–420. ACM (1999)
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
Gonçalves, J.C.d.A., Santoro, F.M., Baiao, F.A.: Business process mining from group stories. In: CSCWD, pp. 161–166. IEEE (2009)
Herbst, J., Karagiannis, D.: An inductive approach to the acquisition and adaptation of workflow models. In: IJCAI, vol. 99, pp. 52–57. Citeseer (1999)
Hildebrandt, T., Mukkamala, R.R., Slaats, T.: Designing a cross-organizational case management system using dynamic condition response graphs. In: EDOC, pp. 161–170 (2011)
Ilieva, M.G., Ormandjieva, O.: Automatic transition of natural language software requirements specification into formal presentation. In: Montoyo, A., Muńoz, R., Métais, E. (eds.) NLDB 2005. LNCS, vol. 3513, pp. 392–397. Springer, Heidelberg (2005). https://doi.org/10.1007/11428817_45
Jurafsky, D., Martin, J.H.: Speech & Language Processing. Pearson Education India, Bengaluru (2000)
Klein, D., Manning, C.D.: Accurate unlexicalized parsing. In: ACL, pp. 423–430 (2003)
Leopold, H., van der Aa, H., Pittke, F., Raffel, M., Mendling, J., Reijers, H.A.: Searching textual and model-based process descriptions based on a unified data format. SoSym 18(2), 1179–1194 (2019)
Leopold, H., van der Aa, H., Reijers, H.A.: Identifying candidate tasks for robotic process automation in textual process descriptions. In: Gulden, J., Reinhartz-Berger, I., Schmidt, R., Guerreiro, S., Guédria, W., Bera, P. (eds.) BPMDS/EMMSAD -2018. LNBIP, vol. 318, pp. 67–81. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-91704-7_5
Maggi, F.M., Di Ciccio, C., Di Francescomarino, C., Kala, T.: Parallel algorithms for the automated discovery of declarative process models. Inf. Syst. 74, 136–152 (2017)
Miller, G.A.: WordNet: a lexical database for English. Commun. ACM 38(11), 39–41 (1995)
Pesic, M., van der Aalst, W.M.P.: A declarative approach for flexible business processes management. In: Eder, J., Dustdar, S. (eds.) BPM 2006. LNCS, vol. 4103, pp. 169–180. Springer, Heidelberg (2006). https://doi.org/10.1007/11837862_18
Riefer, M., Ternis, S.F., Thaler, T.: Mining process models from natural language text: a state-of-the-art analysis. In: MKWI. Universität Illmenau (2016)
Saint-Dizier, P.: Mining incoherent requirements in technical specifications. In: Frasincar, F., Ittoo, A., Nguyen, L.M., Métais, E. (eds.) NLDB 2017. LNCS, vol. 10260, pp. 71–83. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-59569-6_8
Sànchez-Ferreres, J., van der Aa, H., Carmona, J., Padró, L.: Aligning textual and model-based process descriptions. Data Knowl. Eng. 118, 25–40 (2018)
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. IEEE (2010)
Slaats, T., Mukkamala, R.R., Hildebrandt, T., Marquard, M.: Exformatics declarative case management workflows as DCR graphs. In: Daniel, F., Wang, J., Weber, B. (eds.) BPM 2013. LNCS, vol. 8094, pp. 339–354. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-40176-3_28
Weidlich, M., Sheetrit, E., Branco, M.C., Gal, A.: Matching business process models using positional passage-based language models. In: Ng, W., Storey, V.C., Trujillo, J.C. (eds.) ER 2013. LNCS, vol. 8217, pp. 130–137. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-41924-9_12
Winter, K., Rinderle-Ma, S.: Detecting constraints and their relations from regulatory documents using nlp techniques. In: Panetto, H., Debruyne, C., Proper, H., Ardagna, C., Roman, D., Meersman, R. (eds.) OTM 2018. LNCS, vol. 11229, pp. 261–278. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-02610-3_15
Acknowledgments
This work has received funding from the EU H2020 programme under MSCA-RISE agreement 645751 (RISE_BPM) and the Alexander von Humboldt Foundation.
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van der Aa, H., Di Ciccio, C., Leopold, H., Reijers, H.A. (2019). Extracting Declarative Process Models from Natural Language. In: Giorgini, P., Weber, B. (eds) Advanced Information Systems Engineering. CAiSE 2019. Lecture Notes in Computer Science(), vol 11483. Springer, Cham. https://doi.org/10.1007/978-3-030-21290-2_23
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