{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T06:53:51Z","timestamp":1777704831803,"version":"3.51.4"},"reference-count":37,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2020,6,6]],"date-time":"2020-06-06T00:00:00Z","timestamp":1591401600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2020,8,31]]},"abstract":"<jats:p>In this work, we present a model for the automatic generation of written dialogues, through the use of grammatical inference. This model allows the automatic recognition of grammars from a set dialogues employed as a training set. The inferred grammars are then used to generate templates of responses within the dialogues. The final objective is to apply this model in a specific domain dialogue system that answers questions in Spanish with the use of a knowledge base. The experiments carried out have been performend using the DIHANA project corpus which contains dialogues written in Spanish about schedules and prices of a rail system.<\/jats:p>","DOI":"10.3233\/jifs-179876","type":"journal-article","created":{"date-parts":[[2020,6,9]],"date-time":"2020-06-09T12:50:12Z","timestamp":1591707012000},"page":"2105-2113","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Automatic Generation of Dialogues based on Grammatical Inference and the use of a Knowledge Base"],"prefix":"10.1177","volume":"39","author":[{"given":"Andr\u00e9s","family":"V\u00e1zquez","sequence":"first","affiliation":[{"name":"Language &amp; Knowledge Engineering Lab, Benem\u00e9rita Universidad Aut\u00f3noma de Puebla, Puebla, Mexico"}]},{"given":"David","family":"Pinto","sequence":"additional","affiliation":[{"name":"Language &amp; Knowledge Engineering Lab, Benem\u00e9rita Universidad Aut\u00f3noma de Puebla, Puebla, Mexico"}]},{"given":"Juan","family":"Pallares","sequence":"additional","affiliation":[{"name":"Faculty of Computer Science, Benem\u00e9rita Universidad Aut\u00f3noma de Puebla, Puebla, Mexico"}]},{"given":"Rafael","family":"De la Rosa","sequence":"additional","affiliation":[{"name":"Faculty of Computer Science, Benem\u00e9rita Universidad Aut\u00f3noma de Puebla, Puebla, Mexico"}]},{"given":"Elia","family":"Tecotl","sequence":"additional","affiliation":[{"name":"Faculty of Computer Science, Benem\u00e9rita Universidad Aut\u00f3noma de Puebla, Puebla, Mexico"}]}],"member":"179","published-online":{"date-parts":[[2020,6,6]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"crossref","unstructured":"AlvarezG. RuizJ. and Garc\u00edaP. Comparaci\u00f3n de dos algoritmos recientes para inferencia gramatical de lenguajes regulares mediante aut\u00f3matas no deterministas Procesamiento del Lenguaje Natural 2009 pages 21\u201336.","DOI":"10.25100\/iyc.v11i1.2468"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1007\/BF00116828"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1007\/BF00116034"},{"key":"e_1_3_2_5_2","doi-asserted-by":"crossref","unstructured":"BarlierM. P\u00e9rolatJ. LarocheR. and PietquinO. Human-machine dialogue as a stochastic game. In Proceedings of the SIGDIAL 2015 Conference The 16th Annual Meeting of the Special Interest Group on Discourse and Dialogue 2\u20134 September 2015 Prague Czech Republic 2015 pages 2\u201311.","DOI":"10.18653\/v1\/W15-4602"},{"key":"e_1_3_2_6_2","unstructured":"Becerra-BonacheL. On the Learn ability of Mildly Context-Sensitive Languages using Positive Data and Correction Queries. PhD thesis UNIVERSITAT ROVIRA I VIRGILI FACULTAT DE LLETRES DEPARTAMENT DE FILOLOGIES ROMANIQUES 2006."},{"key":"e_1_3_2_7_2","unstructured":"Becerra-BonacheL. Aproximaci\u00f3n de la teor\u00eda de la inferencia gramatical a los estudios de adquisici\u00f3n del lenguaje 2008 pages 327\u2013338."},{"key":"e_1_3_2_8_2","unstructured":"Bened\u00edJ. LieidaE. VaronaA. CastroM. GalianoI. JustoR. De\u00a0LetonaI.L. and AntonioM. Design and acquisition of a telephone spontaneous speech dialogue corpus in spanish: Dihana. In In Fifth LREC 2006 pages 1636\u20131639."},{"key":"e_1_3_2_9_2","doi-asserted-by":"crossref","unstructured":"CarrascoR.C. and OncinaJ. Learning stochastic regular grammars bymeans of a statemergingmethod. In Rafael C. Carrasco and Jose Oncina editors Grammatical Inference and Applications pages 139\u2013152 Berlin Heidelberg 1994. Springer Berlin Heidelberg.","DOI":"10.1007\/3-540-58473-0_144"},{"key":"e_1_3_2_10_2","doi-asserted-by":"crossref","unstructured":"CosteF. FredouilleD. KermorvantC. and De\u00a0la HigueraC. Introducing domain and typing bias in automata inference. In Georgios Paliouras and Yasubumi Sakakibara editors Grammatical Inference: Algorithms and Applications pages 115\u2013126 Berlin Heidelberg 2004. Springer Berlin Heidelberg.","DOI":"10.1007\/978-3-540-30195-0_11"},{"key":"e_1_3_2_11_2","doi-asserted-by":"crossref","unstructured":"CurleyS.S. and HarangR.E. Grammatical inference and machine learning approaches to post-hoc langsec. In 2016 IEEE Security and Privacy Workshops (SPW) IEEE 2016 pages 171\u2013178.","DOI":"10.1109\/SPW.2016.26"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2005.01.003"},{"key":"e_1_3_2_13_2","unstructured":"DusekO. and Jura\u00edcekF. A context-aware natural language generator for dialogue systems CoRR abs\/1608.07076 2016."},{"key":"e_1_3_2_14_2","doi-asserted-by":"crossref","unstructured":"FinkelJ.R. GrenagerT. and ManningC. Incorporating nonlocal information into information extraction systems by gibbs sampling. In Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics ACL \u201905 pages 363\u2013370 Stroudsburg PA USA 2005. Association for Computational Linguistics.","DOI":"10.3115\/1219840.1219885"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0019-9958(67)91165-5"},{"key":"e_1_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0019-9958(78)90562-4"},{"key":"e_1_3_2_17_2","first-page":"213","article-title":"Dos aproximaciones basadas en reglas para la gesti\u00f3n del di\u00e1logo","volume":"35","author":"Griol D.","year":"2005","unstructured":"GriolD., HurtadoL., SanchisE. and SegarraE., Dos aproximaciones basadas en reglas para la gesti\u00f3n del di\u00e1logo, Procesamiento del Lenguaje Natural35 (2005), 213\u2013220.","journal-title":"Procesamiento del Lenguaje Natural"},{"key":"e_1_3_2_18_2","unstructured":"KonstantopoulosS. An embodied dialogue system with personality and emotions. In Proceedings of the 2010 Workshop on Companionable Dialogue Systems pages 31\u201336. Association for Computational Linguistics 2010."},{"key":"e_1_3_2_19_2","doi-asserted-by":"crossref","unstructured":"LiJ. MonroeW. RitterA. JurafskyD. GalleyM. and GaoJ. Deep reinforcement learning for dialogue generation. In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing EMNLP 2016 Austin Texas USA November 1-4 2016 2016 pages 1192\u20131202.","DOI":"10.18653\/v1\/D16-1127"},{"key":"e_1_3_2_20_2","unstructured":"LisonP. Probabilistic dialogue models with prior domain knowledge. In Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue SIGDIAL \u201912 pages 179\u2013188 Stroudsburg PA USA 2012. Association for Computational Linguistics."},{"key":"e_1_3_2_21_2","doi-asserted-by":"crossref","unstructured":"LisonP. Model-based bayesian reinforcement learning for dialogue management CoRR abs\/1304.1819 2013.","DOI":"10.21437\/Interspeech.2013-138"},{"key":"e_1_3_2_22_2","doi-asserted-by":"crossref","unstructured":"LitmanD. and Forbes-RileyK. Evaluating a spoken dialogue system that detects and adapts to user affective states. pages 181\u2013185 January 2014.","DOI":"10.3115\/v1\/W14-4324"},{"key":"e_1_3_2_23_2","unstructured":"MahadikS.K. Dialogue manager for spoken dialogue system : Review. 2017."},{"key":"e_1_3_2_24_2","unstructured":"MisuT. GeorgilaK. LeuskiA. and Traum.D. Reinforcement learning of question-answering dialogue policies for virtual museum guides. In Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue SIGDIAL \u201912 pages 84\u201393 Stroudsburg PA USA 2012. Association for Computational Linguistics."},{"key":"e_1_3_2_25_2","doi-asserted-by":"crossref","unstructured":"PietquinO. Inverse reinforcement learning for interactive systems. In Proceedings of the 2nd Workshop on Machine Learning for Interactive Systems - Bridging the Gap Between Perception Action and Communication MLIS@IJCAI 2013 Beijing China August 4 2013 2013 pages 71\u201375.","DOI":"10.1145\/2493525.2493529"},{"key":"e_1_3_2_26_2","doi-asserted-by":"crossref","unstructured":"PietquinO. Inverse reinforcement learning for interactive systems. In Proceedings of the 2Nd Workshop on Machine Learning for Interactive Systems: Bridging the Gap Between Perception Action and Communication MLIS \u201913 pages 71\u201375 New York NY USA 2013. ACM.","DOI":"10.1145\/2493525.2493529"},{"key":"e_1_3_2_27_2","doi-asserted-by":"crossref","unstructured":"PngS.W. and PineauJ. Bayesian reinforcement learning for pomdp-based dialogue systems. In Proceedings of the IEEE International Conference on Acoustics Speech and Signal Processing ICASSP 2011 May 22-27 2011 Prague Congress Center Prague Czech Republic 2011 pages 2156\u20132159.","DOI":"10.1109\/ICASSP.2011.5946754"},{"issue":"3","key":"e_1_3_2_28_2","first-page":"301","article-title":"Extracting semantic information through automatic learning techniques","volume":"16","author":"Segarra E.","year":"2002","unstructured":"SegarraE., SanchisE., GalianoM., Garc\u00edaF. and HurtadoL.F., Extracting semantic information through automatic learning techniques, IJPRAI16 (3) (2002), 301\u2013307.","journal-title":"IJPRAI"},{"key":"e_1_3_2_29_2","doi-asserted-by":"crossref","unstructured":"SordoniA. GalleyM. AuliM. BrockettC. JiY. MitchellM. NieJ.-Y. GaoJ. and DolanB. A Neural Network Approach to Context-Sensitive Generation of Conversational Responses. pages 196\u2013205 Denver Colorado 2015. Association for Computational Linguistics.","DOI":"10.3115\/v1\/N15-1020"},{"key":"e_1_3_2_30_2","unstructured":"SutskeverI. VinyalsO. and LeQ.V. Sequence to sequence learning with neural networks CoRR abs\/1409.3215 2014."},{"key":"e_1_3_2_31_2","doi-asserted-by":"publisher","DOI":"10.1561\/2200000013"},{"key":"e_1_3_2_32_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2005.148"},{"key":"e_1_3_2_33_2","unstructured":"VinyalsO. and LeQ.V. A neural conversational model CoRR abs\/1506.05869 2015."},{"key":"e_1_3_2_34_2","doi-asserted-by":"crossref","unstructured":"V\u00e1zquezA. PintoD. and Vilari\u00f1oD. Identificaci\u00f3n de etiquetas sem\u00e1nticas para su uso en di\u00e1logos Procesamiento del Lenguaje Natural 2018 pages 99\u2013107.","DOI":"10.13053\/rcs-147-6-7"},{"key":"e_1_3_2_35_2","doi-asserted-by":"crossref","unstructured":"WenT.-H. GasicM. MrksicN. SuP.-H. VandykeD. and YoungS.J. Semantically conditioned lstm-based natural language generation for spoken dialogue systems CoRR abs\/1508.01745 2015.","DOI":"10.18653\/v1\/D15-1199"},{"key":"e_1_3_2_36_2","unstructured":"YaoK. ZweigG. and PengB. Attention with intention for a neural network conversation model CoRR abs\/1510.08565 2015."},{"key":"e_1_3_2_37_2","unstructured":"YokomoriT. Grammatical Inference and Learning pages 507\u2013528. Springer Berlin Heidelberg Berlin Heidelberg 2004."},{"key":"e_1_3_2_38_2","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2012.2225812"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/JIFS-179876","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.3233\/JIFS-179876","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/JIFS-179876","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:42:07Z","timestamp":1777455727000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.3233\/JIFS-179876"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,6]]},"references-count":37,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2020,8,31]]}},"alternative-id":["10.3233\/JIFS-179876"],"URL":"https:\/\/doi.org\/10.3233\/jifs-179876","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,6,6]]}}}