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      Towards Automating the Synthesis of Chatbots for Conversational Model Query

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          Abstract

          Conversational interfaces (also called chatbots) are being increasingly adopted in various domains such as e-commerce or customer service, as a direct communication channel between companies and end-users. Their advantage is that they can be embedded within social networks, and provide a natural language (NL) interface that enables their use by non-technical users. While there are many emerging platforms for building chatbots, their construction remains a highly technical, challenging task.

          In this paper, we propose the use of chatbots to facilitate querying domain-specific models. This way, instead of relying on technical query languages (e.g., OCL), models are queried using NL as this can be more suitable for non-technical users. To avoid manual programming, our solution is based on the automatic synthesis of the model query chatbots from a domain meta-model. These chatbots communicate with an EMF-based modelling backend using the Xatkit framework.

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          Most cited references 7

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          Software Bots

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            Modeling conversational agents for service systems

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              Conversational data exploration

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                Author and article information

                Contributors
                selmin.nurcan@univ-paris1.fr
                iris@is.haifa.ac.il
                spnina@is.haifa.ac.il
                jelenaz@dsv.su.se
                Sara.PerezS@uam.es
                gdaniel@uoc.edu
                jordi.cabot@icrea.cat
                Esther.Guerra@uam.es
                Juan.deLara@uam.es
                Journal
                978-3-030-49418-6
                10.1007/978-3-030-49418-6
                Enterprise, Business-Process and Information Systems Modeling
                Enterprise, Business-Process and Information Systems Modeling
                21st International Conference, BPMDS 2020, 25th International Conference, EMMSAD 2020, Held at CAiSE 2020, Grenoble, France, June 8–9, 2020, Proceedings
                978-3-030-49417-9
                978-3-030-49418-6
                05 May 2020
                2020
                : 387
                : 257-265
                Affiliations
                [6 ]GRID grid.10988.38, ISNI 0000 0001 2173 743X, University Paris 1, ; Paris, France
                [7 ]GRID grid.18098.38, ISNI 0000 0004 1937 0562, University of Haifa, ; Haifa, Israel
                [8 ]GRID grid.18098.38, ISNI 0000 0004 1937 0562, University of Haifa, ; Haifa, Israel
                [9 ]GRID grid.10548.38, ISNI 0000 0004 1936 9377, Stockholm University, ; Kista, Sweden
                [10 ]GRID grid.5515.4, ISNI 0000000119578126, Universidad Autónoma de Madrid, ; Madrid, Spain
                [11 ]GRID grid.36083.3e, ISNI 0000 0001 2171 6620, Universitat Oberta de Catalunya, ; Barcelona, Spain
                [12 ]GRID grid.425902.8, ISNI 0000 0000 9601 989X, ICREA, ; Barcelona, Spain
                Article
                17
                10.1007/978-3-030-49418-6_17
                7254563
                © Springer Nature Switzerland AG 2020

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

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                © Springer Nature Switzerland AG 2020

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