{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T15:51:56Z","timestamp":1773330716463,"version":"3.50.1"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"20","license":[{"start":{"date-parts":[[2022,5,28]],"date-time":"2022-05-28T00:00:00Z","timestamp":1653696000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,5,28]],"date-time":"2022-05-28T00:00:00Z","timestamp":1653696000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100003593","name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003593","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004586","name":"Funda\u00e7\u00e3o Carlos Chagas Filho de Amparo \u00e0 Pesquisa do Estado do Rio de Janeiro","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004586","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2022,10]]},"DOI":"10.1007\/s00521-022-07383-2","type":"journal-article","created":{"date-parts":[[2022,5,28]],"date-time":"2022-05-28T13:05:41Z","timestamp":1653743141000},"page":"17381-17406","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["User intent classification in noisy texts: an investigation on neural language models"],"prefix":"10.1007","volume":"34","author":[{"given":"Patrick","family":"Blackman Sphaier","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9089-7303","authenticated-orcid":false,"given":"Aline","family":"Paes","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,5,28]]},"reference":[{"key":"7383_CR1","doi-asserted-by":"crossref","unstructured":"Litman DJ, Walker MA, Kearns MS (1999) Automatic detection of poor speech recognition at the dialogue level. In: Proc. of the 37th annual meeting of the association for computational linguistics on computational linguistics, pp 309\u2013316. ACL","DOI":"10.3115\/1034678.1034729"},{"issue":"1","key":"7383_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1017\/S1351324912000332","volume":"20","author":"E Mart\u00ednez-C\u00e1mara","year":"2014","unstructured":"Mart\u00ednez-C\u00e1mara E, Mart\u00edn-Valdivia MT, Urena-L\u00f3pez LA, Montejo-R\u00e1ez AR (2014) Sentiment analysis in twitter. Nat Lang Eng 20(1):1\u201328","journal-title":"Nat Lang Eng"},{"key":"7383_CR3","unstructured":"Wen T-H, Miao Y, Blunsom P, Young S (2017) Latent intention dialogue models. In: Proc. of the 34th international conference on machine learning-Volume 70, pp 3732\u20133741. JMLR. org"},{"key":"7383_CR4","unstructured":"Pak A, Paroubek P (2010) Twitter as a corpus for sentiment analysis and opinion mining. In: Proceedings of the international conference on language resources and evaluation, LREC 2010. ELRA"},{"key":"7383_CR5","unstructured":"Akbik A, Bergmann T, Blythe D, Rasul K, Schweter S, Vollgraf R (2019) Flair: An easy-to-use framework for state-of-the-art NLP. In: Proc. of the 2019 conference of the North American chapter of the association for computational linguistics (Demonstrations), pp 54\u201359"},{"key":"7383_CR6","unstructured":"Mikolov T, Chen K, Corrado G, Dean J (2013) Efficient estimation of word representations in vector space. In: Bengio, Y., LeCun, Y. (eds.) 1st international conference on learning representations, ICLR 2013"},{"key":"7383_CR7","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1162\/tacl_a_00051","volume":"5","author":"P Bojanowski","year":"2017","unstructured":"Bojanowski P, Grave E, Joulin A, Mikolov T (2017) Enriching word vectors with subword information. Trans Assoc Comput Linguist 5:135\u2013146","journal-title":"Trans Assoc Comput Linguist"},{"key":"7383_CR8","unstructured":"Mikolov T, Grave E, Bojanowski P, Puhrsch C, Joulin A (2018) Advances in pre-training distributed word representations. In: Proc. of the eleventh international conference on language resources and evaluation (LREC 2018). ELRA"},{"key":"7383_CR9","doi-asserted-by":"crossref","unstructured":"Peters ME, Neumann M, Iyyer M, Gardner M, Clark C, Lee K, Zettlemoyer L (2018) Deep contextualized word representations. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2018, Volume 1 (Long Papers), pp 2227\u20132237. ACL","DOI":"10.18653\/v1\/N18-1202"},{"key":"7383_CR10","unstructured":"Devlin J, Chang M, Lee K, Toutanova K (2019) BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT, pp 4171\u20134186. ACL"},{"key":"7383_CR11","doi-asserted-by":"crossref","unstructured":"Howard J, Ruder S (2018) Universal language model fine-tuning for text classification. In: Proc. of the 56th annual meeting of the association for computational linguistics (Volume 1: Long Papers), pp 328\u2013339","DOI":"10.18653\/v1\/P18-1031"},{"key":"7383_CR12","unstructured":"Kalchbrenner N, Blunsom P (2013) Recurrent convolutional neural networks for discourse compositionality. In: Proceedings of the workshop on continuous vector space models and their compositionality, CVSM@ACL 2013, pp 119\u2013126"},{"key":"7383_CR13","doi-asserted-by":"crossref","unstructured":"Lee JY, Dernoncourt F (2016) Sequential short-text classification with recurrent and convolutional neural networks. In: NAACL HLT 2016, The 2016 conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp 515\u2013520","DOI":"10.18653\/v1\/N16-1062"},{"key":"7383_CR14","doi-asserted-by":"crossref","unstructured":"Mahgoub A, Shahin Y, Mansour R, Bagchi S (2019) Simvecs: Similarity-based vectors for utterance representation in conversational AI systems. In: Proceedings of the 23rd conference on computational natural language learning, CoNLL 2019, pp 708\u2013717. ACL","DOI":"10.18653\/v1\/K19-1066"},{"key":"7383_CR15","unstructured":"Chen Q, Zhuo Z, Wang W (2019) BERT for joint intent classification and slot filling. CoRR arXiv:abs\/1902.10909"},{"issue":"11","key":"7383_CR16","doi-asserted-by":"publisher","first-page":"613","DOI":"10.1145\/361219.361220","volume":"18","author":"G Salton","year":"1975","unstructured":"Salton G, Wong A, Yang CS (1975) A vector space model for automatic indexing. Commun ACM 18(11):613\u2013620","journal-title":"Commun ACM"},{"key":"7383_CR17","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1613\/jair.2934","volume":"37","author":"PD Turney","year":"2010","unstructured":"Turney PD, Pantel P (2010) From frequency to meaning: vector space models of semantics. J Artif Intell Res 37:141\u2013188","journal-title":"J Artif Intell Res"},{"key":"7383_CR18","first-page":"77","volume-title":"Parallel distributed processing: explorations in the microstructure of cognition","author":"GE Hinton","year":"1986","unstructured":"Hinton GE, McClelland JL, Rumelhart DE (1986) Distributed representations. In: Rumelhart DE, McClelland JL, PDP Research\u00a0Group C (eds) Parallel distributed processing: explorations in the microstructure of cognition, vol 1. MIT Press, Cambridge, pp 77\u2013109"},{"key":"7383_CR19","doi-asserted-by":"crossref","unstructured":"Pennington J, Socher R, Manning CD (2014) Glove: Global vectors for word representation. In: Proceedings of the 2014 Conference on empirical methods in natural language processing, EMNLP 2014, October 25-29, 2014, Doha, Qatar, A Meeting of SIGDAT, a Special Interest Group of The ACL, pp 1532\u20131543. ACL","DOI":"10.3115\/v1\/D14-1162"},{"key":"7383_CR20","doi-asserted-by":"crossref","unstructured":"Chelba C, Mikolov T, Schuster M, Ge Q, Brants T, Koehn P, Robinson T (2014) One billion word benchmark for measuring progress in statistical language modeling. In: INTERSPEECH 2014, 15th annual conference of the international speech communication association, pp 2635\u20132639. ISCA","DOI":"10.21437\/Interspeech.2014-564"},{"key":"7383_CR21","unstructured":"Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser L, Polosukhin I (2017) Attention is all you need. In: Advances in neural information processing systems 30: annual conference on neural information processing systems, pp 5998\u20136008"},{"key":"7383_CR22","unstructured":"Wu Y, Schuster M, Chen Z, Le QV, Norouzi M, Macherey W, Krikun M, Cao Y, Gao Q, Macherey K, Klingner J, Shah A, Johnson M, Liu X, \u0141ukasz Kaiser, Gouws S, Kato Y, Kudo T, Kazawa H, Stevens K, Kurian G, Patil N, Wang W, Young C, Smith J, Riesa J, Rudnick A, Vinyals O, Corrado G, Hughes M, Dean J (2016) Google\u2019s neural machine translation system: bridging the gap between human and machine translation"},{"key":"7383_CR23","unstructured":"Ruder S (2019) Neural transfer learning for natural language processing. PhD thesis, National University of Ireland, Galway"},{"key":"7383_CR24","unstructured":"Merity S, Xiong C, Bradbury J, Socher R (2017) Pointer sentinel mixture models. In: 5th international conference on learning representations, ICLR 2017, Conference track proceedings. OpenReview.net"},{"key":"7383_CR25","unstructured":"Merity S, Keskar NS, Socher R (2018) Regularizing and optimizing LSTM language models. In: 6th international conference on learning representations, ICLR 2018, conference track proceedings. OpenReview.net"},{"key":"7383_CR26","doi-asserted-by":"crossref","unstructured":"Gururangan S, Marasovic A, Swayamdipta S, Lo K, Beltagy I, Downey D, Smith NA (2020) Don\u2019t stop pretraining: adapt language models to domains and tasks. In: Proceedings of the 58th annual meeting of the association for computational linguistics, ACL 2020, pp 8342\u20138360. ACL","DOI":"10.18653\/v1\/2020.acl-main.740"},{"key":"7383_CR27","doi-asserted-by":"crossref","unstructured":"Zhu Y, Kiros R, Zemel RS, Salakhutdinov R, Urtasun R, Torralba A, Fidler S (2015) Aligning books and movies: towards story-like visual explanations by watching movies and reading books. In: 2015 IEEE international conference on computer vision, ICCV 2015, pp. 19\u201327. IEEE Computer Society","DOI":"10.1109\/ICCV.2015.11"},{"key":"7383_CR28","doi-asserted-by":"crossref","unstructured":"Souza F, Nogueira R, de Alencar\u00a0Lotufo R (2020) Bertimbau: pretrained BERT models for brazilian portuguese. In: Intelligent systems - 9th Brazilian Conference, BRACIS 2020, Proceedings, Part I. lecture notes in computer science, vol 12319, pp 403\u2013417. Springer","DOI":"10.1007\/978-3-030-61377-8_28"},{"key":"7383_CR29","unstructured":"Wagner\u00a0Filho JA, Wilkens R, Idiart M, Villavicencio A (2018) The brWaC corpus: a new open resource for Brazilian Portuguese. In: Proceedings of the eleventh international conference on language resources and evaluation (LREC 2018). ELRA"},{"key":"7383_CR30","doi-asserted-by":"crossref","unstructured":"Liu X, Eshghi A, Swietojanski P, Rieser V (2019) Benchmarking natural language understanding services for building conversational agents. In: Increasing naturalness and flexibility in spoken dialogue interaction - 10th international workshop on spoken dialogue systems, IWSDS. Lecture notes in electrical engineering, vol 714, pp 165\u2013183. Springer","DOI":"10.1007\/978-981-15-9323-9_15"},{"key":"7383_CR31","unstructured":"Hartmann N, Fonseca E, Shulby C, Treviso M, Silva J, Alu\u00edsio S (2017) Portuguese word embeddings: evaluating on word analogies and natural language tasks. In: Proceedings of the 11th Brazilian symposium in information and human language technology, pp 122\u2013131. Sociedade Brasileira de Computa\u00e7\u00e3o, Uberl\u00e2ndia, Brazil. https:\/\/aclanthology.org\/W17-6615"},{"key":"7383_CR32","doi-asserted-by":"crossref","unstructured":"Rodrigues RC, Rodrigues J, de Castro PVQ, da Silva NFF, Soares A (2020) Portuguese language models and word embeddings: evaluating on semantic similarity tasks. In: Computational processing of the Portuguese Language, pp 239\u2013248. Springer","DOI":"10.1007\/978-3-030-41505-1_23"},{"key":"7383_CR33","doi-asserted-by":"crossref","unstructured":"Wolf T, Debut L, Sanh V, Chaumond J, Delangue C, Moi A, Cistac P, Rault T, Louf R, Funtowicz M, Davison J, Shleifer S, von Platen P, Ma C, Jernite Y, Plu J, Xu C, Scao TL, Gugger S, Drame M, Lhoest Q, Rush AM (2020) Transformers: state-of-the-art natural language processing. In: Liu Q, Schlangen D (eds) Proceedings of the 2020 conference on empirical methods in natural language processing: system demonstrations, EMNLP 2020 - Demos, pp 38\u201345","DOI":"10.18653\/v1\/2020.emnlp-demos.6"},{"key":"7383_CR34","unstructured":"Kokhlikyan N, Miglani V, Martin M, Wang E, Alsallakh B, Reynolds J, Melnikov A, Kliushkina N, Araya C, Yan S, Reblitz-Richardson O (2020) Captum: a unified and generic model interpretability library for pytorch. CoRR arXiv:abs\/2009.07896"},{"key":"7383_CR35","doi-asserted-by":"crossref","unstructured":"Ribeiro E, Ribeiro R, de Matos DM (2018) A study on dialog act recognition using character-level tokenization. In: Artificial intelligence: methodology, systems, and applications: 18th international conference, AIMSA. Lecture notes in computer science, vol 11089, pp 93\u2013103","DOI":"10.1007\/978-3-319-99344-7_9"},{"key":"7383_CR36","unstructured":"Zhang X, Zhao JJ, LeCun Y (2015) Character-level convolutional networks for text classification. In: Advances in neural information processing systems 28: annual conference on neural information processing systems 2015, pp 649\u2013657"},{"key":"7383_CR37","doi-asserted-by":"crossref","unstructured":"Braun D, Hernandez-Mendez A, Matthes F, Langen M (2017) Evaluating natural language understanding services for conversational question answering systems. In: Proceedings of the 18th annual SIGdial meeting on discourse and dialogue, pp 174\u2013185","DOI":"10.18653\/v1\/W17-5522"},{"key":"7383_CR38","doi-asserted-by":"crossref","unstructured":"Coucke A, Saade A, Ball A, Bluche T, Caulier A, Leroy D, Doumouro C, Gisselbrecht T, Caltagirone F, Lavril T, Primet M, Dureau J (2018) Snips voice platform: an embedded spoken language understanding system for private-by-design voice interfaces. CoRR arXiv:abs\/1805.10190","DOI":"10.1109\/EMC2-NIPS53020.2019.00021"},{"key":"7383_CR39","doi-asserted-by":"crossref","unstructured":"Nigam A, Sahare P, Pandya K (2019) Intent detection and slots prompt in a closed-domain chatbot. In: 2019 IEEE 13th international conference on semantic computing (ICSC), pp 340\u2013343","DOI":"10.1109\/ICOSC.2019.8665635"},{"key":"7383_CR40","doi-asserted-by":"publisher","unstructured":"Joshi P, Santy S, Budhiraja A, Bali K, Choudhury M (2020) The state and fate of linguistic diversity and inclusion in the NLP world. In: Proceedings of the 58th annual meeting of the association for computational linguistics. https:\/\/doi.org\/10.18653\/v1\/2020.acl-main.560","DOI":"10.18653\/v1\/2020.acl-main.560"},{"key":"7383_CR41","doi-asserted-by":"crossref","unstructured":"Swayamdipta S, Schwartz R, Lourie N, Wang Y, Hajishirzi H, Smith NA, Choi Y (2020) Dataset cartography: Mapping and diagnosing datasets with training dynamics. In: Proceedings of the 2020 conference on empirical methods in natural language processing, EMNLP 2020, pp 9275\u20139293. ACL","DOI":"10.18653\/v1\/2020.emnlp-main.746"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-022-07383-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-022-07383-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-022-07383-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,23]],"date-time":"2022-09-23T15:14:08Z","timestamp":1663946048000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-022-07383-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,28]]},"references-count":41,"journal-issue":{"issue":"20","published-print":{"date-parts":[[2022,10]]}},"alternative-id":["7383"],"URL":"https:\/\/doi.org\/10.1007\/s00521-022-07383-2","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,5,28]]},"assertion":[{"value":"3 November 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 April 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 May 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The second author has financial grants issued by the Brazilian Governmental Research Agencies CNPq and FAPERJ. We certify that there is no actual or potential conflict of interest in relation to this manuscript.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of Interest"}}]}}