Abstract
Decision models are the consolidated knowledge representation of the requirements and the logic of operational decisions in business organizations. Decision models defined in the Decision Model and Notation (DMN) standard can contribute significantly to the automation of business decision management. However, the current scope of decision support is quite limited in presenting the decision-making process to an end-user in a reliable, user-friendly way. This paper provides a framework for automatically generating chatbots from DMN models that can handle numerous user scenarios for effective and explainable decision-making during customer support inquiries. The method can improve the digitalization of customer services and give customers more transparency and trust in the decision-making through user-friendly chatbots.
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
Similar content being viewed by others
References
Aerts, B., Vandevelde, S., Vennekens, J.: Tackling the DMN challenges with cDMN: a tight integration of DMN and constraint reasoning. In: Gutiérrez-Basulto, V., Kliegr, T., Soylu, A., Giese, M., Roman, D. (eds.) RuleML+RR 2020. LNCS, vol. 12173, pp. 23–38. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-57977-7_2
Al-Zubaide, H., Issa, A.A.: OntBot: ontology based ChatBot. In: 2011 4th International Symposium on Innovation in Information and Communication Technology, ISIICT 2011, pp. 7–12 (2011). https://doi.org/10.1109/ISIICT.2011.6149594
Androutsopoulou, A., Karacapilidis, N., Loukis, E., Charalabidis, Y.: Transforming the communication between citizens and government through AI-guided chatbots. Gov. Inf. Q. 36(2), 358–367 (2019)
Dale, R.: The return of the chatbots. Nat. Lang. Eng. 22(5), 811–817 (2016). https://doi.org/10.1017/S1351324916000243
Dasseville, I., Janssens, L., Janssens, G., Vanthienen, J., Denecker, M.: Combining DMN and the knowledge base paradigm for flexible decision enactment. In: Supplementary Proceedings of the RuleML 2016 Challenge, vol. 1620 (2016)
Etikala, V., Van Veldhoven, Z., Vanthienen, J.: Text2Dec: extracting decision dependencies from natural language text for automated DMN decision modelling. In: Del Río Ortega, A., Leopold, H., Santoro, F.M. (eds.) BPM 2020. LNBIP, vol. 397, pp. 367–379. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-66498-5_27
Figl, K., Mendling, J., Tokdemir, G., Vanthienen, J.: What we know and what we do not know about DMN. Enterp. Model. Inf. Syst. Archit. Int. J. Concept. Model. 13(2), 1–16 (2018)
Hussain, S., Ameri Sianaki, O., Ababneh, N.: A survey on conversational agents/chatbots classification and design techniques. In: Barolli, L., Takizawa, M., Xhafa, F., Enokido, T. (eds.) WAINA 2019. AISC, vol. 927, pp. 946–956. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-15035-8_93
Huysmans, J., Dejaeger, K., Mues, C., Vanthienen, J., Baesens, B.: An empirical evaluation of the comprehensibility of decision table, tree and rule based predictive models. Decis. Support Syst. 51(1), 141–154 (2011)
Janssen, A., Rodríguez Cardona, D., Breitner, M.H., et al.: More than FAQ! Chatbot taxonomy for business-to-business customer services. In: Følstad, A. (ed.) CONVERSATIONS 2020. LNCS, vol. 12604, pp. 175–189. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-68288-0_12
Jia, J.: The study of the application of a keywords-based chatbot system on the teaching of foreign languages, pp. 1–11 (2003)
Kang, Y., Cai, Z., Tan, C.W., Huang, Q., Liu, H.: Natural language processing (NLP) in management research: a literature review. J. Manag. Anal. 7(2), 139–172 (2020)
von Leipzig, T., et al.: Initialising customer-orientated digital transformation in enterprises. Proc. Manuf. 8, 517–524 (2017). https://doi.org/10.1016/j.promfg.2017.02.066
López, A., Sànchez-Ferreres, J., Carmona, J., Padró, L.: From process models to chatbots. In: Giorgini, P., Weber, B. (eds.) CAiSE 2019. LNCS, vol. 11483, pp. 383–398. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-21290-2_24
Van Veldhoven, Z., Vanthienen, J.: Digital transformation as an interaction-driven perspective between business, society, and technology. Electron. Mark. 16 (2021). https://doi.org/10.1007/s12525-021-00464-5
Vanthienen, J.: On smart data, decisions and processes. In: 2015 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K), vol. 1, p. 5. IEEE (2015)
Vanthienen, J.: Decisions, advice and explanation: an overview and research agenda. In: A Research Agenda for Knowledge Management and Analytics (2021)
Vanthienen, J., Mues, C., Aerts, A.: An illustration of verification and validation in the modelling phase of KBS development. Data Knowl. Eng. 27(3), 337–352 (1998)
Zierau, N., Elshan, E., Visini, C., Janson, A.: A review of the empirical literature on conversational agents and future research directions. In: International Conference on Information Systems (ICIS) (2020)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Etikala, V., Goossens, A., Van Veldhoven, Z., Vanthienen, J. (2021). Automatic Generation of Intelligent Chatbots from DMN Decision Models. In: Moschoyiannis, S., Peñaloza, R., Vanthienen, J., Soylu, A., Roman, D. (eds) Rules and Reasoning. RuleML+RR 2021. Lecture Notes in Computer Science(), vol 12851. Springer, Cham. https://doi.org/10.1007/978-3-030-91167-6_10
Download citation
DOI: https://doi.org/10.1007/978-3-030-91167-6_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-91166-9
Online ISBN: 978-3-030-91167-6
eBook Packages: Computer ScienceComputer Science (R0)