Towards versatile conversations with data-driven dialog management and its integration in commercial platforms Cañas, Pablo Griol Barres, David Callejas Carrión, Zoraida Conversational systems Deep learning Dialog management DialogFlow Statistical approaches The research leading to these results has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement no. 823907 (MENHIR project: https://menhir-project.eu) and the Spanish project PID2020-118112RB-C21. Funding for open access charge: Universidad de Granada / CBUA. Conversational interfaces have recently become a ubiquitous element in both the personal sphere by easing access to services, and industrial environments by the automation of services, improved customer support and its corresponding cost savings. However, designing the dialog model used by these interfaces to decide system responses is still a hard-to-accomplish task for complex conversational interactions. This paper describes a data-driven dialog management technique, which provides flexibility to develop, deploy and maintain this module. Various configurations for classification algorithms are assessed with two dialog corpora of different application domains, size, dimensionalities and set of possible system responses. The results of the evaluation show satisfactory accuracy and coherence rates in both tasks. As a proof of concept, our proposal has also been integrated with DialogFlow, a platform provided by Google to design conversational user interfaces. Our proposal has been assessed with a real use case, proving that it can be deployed in conjunction with commercial platforms, obtaining satisfactory results for the objective and subjective assessments completed. 2021-10-29T11:45:35Z 2021-10-29T11:45:35Z 2021-10 journal article Canas, P. [et al.] Towards versatile conversations with data-driven dialog management and its integration in commercial platforms. Journal of Computational Science 55 (2021) 101443. [https://doi.org/10.1016/j.jocs.2021.101443] http://hdl.handle.net/10481/71177 10.1016/j.jocs.2021.101443 eng http://creativecommons.org/licenses/by-nc-nd/3.0/es/ open access Atribución-NoComercial-SinDerivadas 3.0 España Elsevier