{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T17:36:13Z","timestamp":1777656973088,"version":"3.51.4"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"22","license":[{"start":{"date-parts":[[2024,4,22]],"date-time":"2024-04-22T00:00:00Z","timestamp":1713744000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,4,22]],"date-time":"2024-04-22T00:00:00Z","timestamp":1713744000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Excellent Doctoral Student Research Innovation Project of Xinjiang University","award":["XJU2022BS077"],"award-info":[{"award-number":["XJU2022BS077"]}]},{"name":"Opening Project of Key Laboratory of Xinjiang, China","award":["2020D04047"],"award-info":[{"award-number":["2020D04047"]}]},{"DOI":"10.13039\/501100012166","name":"National Key R &D Program of China","doi-asserted-by":"crossref","award":["2020AAA0107902"],"award-info":[{"award-number":["2020AAA0107902"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61663044"],"award-info":[{"award-number":["61663044"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2024,8]]},"DOI":"10.1007\/s00521-024-09733-8","type":"journal-article","created":{"date-parts":[[2024,4,22]],"date-time":"2024-04-22T13:01:31Z","timestamp":1713790891000},"page":"13513-13525","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["CEA-Net: a co-interactive external attention network for joint intent detection and slot filling"],"prefix":"10.1007","volume":"36","author":[{"given":"Di","family":"Wu","sequence":"first","affiliation":[]},{"given":"Liting","family":"Jiang","sequence":"additional","affiliation":[]},{"given":"Lili","family":"Yin","sequence":"additional","affiliation":[]},{"given":"Zhe","family":"Li","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6604-0951","authenticated-orcid":false,"given":"Hao","family":"Huang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,4,22]]},"reference":[{"key":"9733_CR1","doi-asserted-by":"publisher","DOI":"10.1002\/9781119992691","volume-title":"Spoken language understanding: systems for extracting semantic information from speech","author":"G Tur","year":"2011","unstructured":"Tur G, De Mori R (2011) Spoken language understanding: systems for extracting semantic information from speech. John Wiley and Sons, Hoboken"},{"issue":"3","key":"9733_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3439726","volume":"54","author":"S Minaee","year":"2021","unstructured":"Minaee S, Kalchbrenner N, Cambria E, Nikzad N, Chenaghlu M, Gao J (2021) Deep learning-based text classification: a comprehensive review. ACM Comput Surv (CSUR) 54(3):1\u201340","journal-title":"ACM Comput Surv (CSUR)"},{"key":"9733_CR3","doi-asserted-by":"crossref","unstructured":"Nguyen N, Guo Y (2007) Comparisons of sequence labeling algorithms and extensions. In: Proceedings of the 24th International Conference on Machine Learning, pp 681\u2013688","DOI":"10.1145\/1273496.1273582"},{"issue":"8","key":"9733_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3547138","volume":"55","author":"H Weld","year":"2022","unstructured":"Weld H, Huang X, Long S, Poon J, Han SC (2022) A survey of joint intent detection and slot filling models in natural language understanding. ACM Comput Surv 55(8):1\u201338","journal-title":"ACM Comput Surv"},{"key":"9733_CR5","doi-asserted-by":"crossref","unstructured":"Hakkani-T\u00fcr D, Celikyilmaz A, Chen Y-N, Gao J, Deng L, Wang Y-Y (2016) Multi-domain joint semantic frame parsing using bi-directional rnn-lstm. In: Seventeenth Annual Conference of the International Speech Communication Association, pp 715\u2013719","DOI":"10.21437\/Interspeech.2016-402"},{"key":"9733_CR6","doi-asserted-by":"crossref","unstructured":"Liu B, Lane I (2016) Joint online spoken language understanding and language modeling with recurrent neural networks. In: Proceedings of the 17th Annual Meeting of the Special Interest Group on Discourse and Dialogue, pp 22\u201330","DOI":"10.18653\/v1\/W16-3603"},{"key":"9733_CR7","doi-asserted-by":"crossref","unstructured":"Qin L, Che W, Li Y, Wen H, Liu T (2019) A stack-propagation framework with token-level intent detection for spoken language understanding. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pp 2078\u20132087","DOI":"10.18653\/v1\/D19-1214"},{"key":"9733_CR8","unstructured":"Haihong E, Niu P, Chen Z, Song M (2019) A novel bi-directional interrelated model for joint intent detection and slot filling. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp 5467\u20135471"},{"key":"9733_CR9","doi-asserted-by":"crossref","unstructured":"Qin L, tianbao X, Che W, Liu T (2021) A survey on spoken language understanding: recent advances and new frontiers. In: Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI-21), pp 4577\u20134584","DOI":"10.24963\/ijcai.2021\/622"},{"key":"9733_CR10","doi-asserted-by":"crossref","unstructured":"Zhou P, Huang Z, Liu F, Zou Y (2021) Pin: a novel parallel interactive network for spoken language understanding. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp 2950\u20132957. IEEE","DOI":"10.1109\/ICPR48806.2021.9411948"},{"key":"9733_CR11","doi-asserted-by":"crossref","unstructured":"Qin L, Liu T, Che W, Kang B, Zhao S, Liu T (2021) A co-interactive transformer for joint slot filling and intent detection. In: ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp 8193\u20138197. IEEE","DOI":"10.1109\/ICASSP39728.2021.9414110"},{"key":"9733_CR12","doi-asserted-by":"crossref","unstructured":"Guo M-H, Liu Z-N, Mu T-J, Hu S-M (2022) Beyond self-attention: external attention using two linear layers for visual tasks. IEEE Transactions on Pattern Analysis and Machine Intelligence","DOI":"10.1109\/TPAMI.2022.3211006"},{"key":"9733_CR13","doi-asserted-by":"crossref","unstructured":"Chelba C, Mahajan M, Acero A (2003) Speech utterance classification. In: 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings.(ICASSP\u201903), vol 1, p IEEE","DOI":"10.1109\/ICASSP.2003.1198772"},{"key":"9733_CR14","doi-asserted-by":"crossref","unstructured":"Xu P, Sarikaya R (2013) Convolutional neural network based triangular crf for joint intent detection and slot filling. In: 2013 IEEE Workshop on Automatic Speech Recognition and Understanding, pp 78\u201383. IEEE","DOI":"10.1109\/ASRU.2013.6707709"},{"key":"9733_CR15","doi-asserted-by":"crossref","unstructured":"Xia C, Zhang C, Yan X, Chang Y, Philip SY (2018) Zero-shot user intent detection via capsule neural networks. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 3090\u20133099","DOI":"10.18653\/v1\/D18-1348"},{"key":"9733_CR16","doi-asserted-by":"crossref","unstructured":"Ravuri S, Stolcke A (2015) Recurrent neural network and lstm models for lexical utterance classification. In: Sixteenth Annual Conference of the International Speech Communication Association, pp 135\u2013139","DOI":"10.21437\/Interspeech.2015-42"},{"key":"9733_CR17","doi-asserted-by":"crossref","unstructured":"Mesnil G, He X, Deng L, Bengio Y (2013) Investigation of recurrent-neural-network architectures and learning methods for spoken language understanding. In: Interspeech, pp 3771\u20133775","DOI":"10.21437\/Interspeech.2013-596"},{"key":"9733_CR18","doi-asserted-by":"crossref","unstructured":"Vu NT, Gupta P, Adel H, Sch\u00fctze H (2016) Bi-directional recurrent neural network with ranking loss for spoken language understanding. In: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp 6060\u20136064. IEEE","DOI":"10.1109\/ICASSP.2016.7472841"},{"issue":"3","key":"9733_CR19","doi-asserted-by":"publisher","first-page":"530","DOI":"10.1109\/TASLP.2014.2383614","volume":"23","author":"G Mesnil","year":"2014","unstructured":"Mesnil G, Dauphin Y, Yao K, Bengio Y, Deng L, Hakkani-Tur D, He X, Heck L, Tur G, Yu D et al (2014) Using recurrent neural networks for slot filling in spoken language understanding. IEEE\/ACM Trans Audio Speech Lang Process 23(3):530\u2013539","journal-title":"IEEE\/ACM Trans Audio Speech Lang Process"},{"issue":"16","key":"9733_CR20","doi-asserted-by":"publisher","first-page":"13639","DOI":"10.1007\/s00521-022-07171-y","volume":"34","author":"C Li","year":"2022","unstructured":"Li C, Zhou Y, Chao G, Chu D (2022) Understanding users\u2019 requirements precisely: a double bi-lstm-crf joint model for detecting user\u2019s intentions and slot tags. Neural Comput Appl 34(16):13639\u201313648","journal-title":"Neural Comput Appl"},{"key":"9733_CR21","first-page":"2993","volume":"16","author":"X Zhang","year":"2016","unstructured":"Zhang X, Wang H (2016) A joint model of intent determination and slot filling for spoken language understanding. IJCAI 16:2993\u20132999","journal-title":"IJCAI"},{"key":"9733_CR22","doi-asserted-by":"crossref","unstructured":"Liu B, Lane IR (2016) Attention-based recurrent neural network models for joint intent detection and slot filling. In: Fourteenth Annual Conference of the International Speech Communication Association, pp 685\u2013689","DOI":"10.21437\/Interspeech.2016-1352"},{"key":"9733_CR23","unstructured":"Ma Z, Sun B, Li S (2022) A two-stage selective fusion framework for joint intent detection and slot filling. IEEE Transactions on Neural Networks and Learning Systems"},{"key":"9733_CR24","doi-asserted-by":"crossref","unstructured":"Goo C-W, Gao G, Hsu Y-K, Huo C-L, Chen T-C, Hsu K-W, Chen Y-N (2018) Slot-gated modeling for joint slot filling and intent prediction. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers), pp 753\u2013757","DOI":"10.18653\/v1\/N18-2118"},{"key":"9733_CR25","doi-asserted-by":"crossref","unstructured":"Li C, Li L, Qi J (2018) A self-attentive model with gate mechanism for spoken language understanding. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp 3824\u20133833","DOI":"10.18653\/v1\/D18-1417"},{"key":"9733_CR26","doi-asserted-by":"crossref","unstructured":"Wang Y, Shen Y, Jin H (2018) A bi-model based rnn semantic frame parsing model for intent detection and slot filling. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers), pp 309\u2013314","DOI":"10.18653\/v1\/N18-2050"},{"key":"9733_CR27","doi-asserted-by":"crossref","unstructured":"Zhang C, Li Y, Du N, Fan W, Philip SY (2019) Joint slot filling and intent detection via capsule neural networks. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp 5259\u20135267","DOI":"10.18653\/v1\/P19-1519"},{"key":"9733_CR28","doi-asserted-by":"crossref","unstructured":"Liu Y, Meng F, Zhang J, Zhou J, Chen Y, Xu J (2019) Cm-net: A novel collaborative memory network for spoken language understanding. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pp 1051\u20131060","DOI":"10.18653\/v1\/D19-1097"},{"issue":"8","key":"9733_CR29","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter S, Schmidhuber J (1997) Long short-term memory. Neural Comput 9(8):1735\u20131780","journal-title":"Neural Comput"},{"key":"9733_CR30","doi-asserted-by":"crossref","unstructured":"Cui L, Zhang Y (2019) Hierarchically-refined label attention network for sequence labeling. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pp 4115\u20134128","DOI":"10.18653\/v1\/D19-1422"},{"key":"9733_CR31","unstructured":"Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser \u0141, Polosukhin I (2017) Attention is all you need. Adv Neural Inform Process Syst 30"},{"key":"9733_CR32","doi-asserted-by":"crossref","unstructured":"Kim Y (2014) Convolutional neural networks for sentence classification. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp 1746\u20131751. Association for Computational Linguistics, Doha, Qatar","DOI":"10.3115\/v1\/D14-1181"},{"key":"9733_CR33","doi-asserted-by":"crossref","unstructured":"Lample G, Ballesteros M, Subramanian S, Kawakami K, Dyer C (2016) Neural architectures for named entity recognition. In: Proceedings of NAACL-HLT, pp 260\u2013270","DOI":"10.18653\/v1\/N16-1030"},{"key":"9733_CR34","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. arXiv:abs\/1805.10190","DOI":"10.1109\/EMC2-NIPS53020.2019.00021"},{"key":"9733_CR35","doi-asserted-by":"crossref","unstructured":"Hemphill CT, Godfrey JJ, Doddington GR (1990) The atis spoken language systems pilot corpus. In: Speech and Natural Language: Proceedings of a Workshop Held at Hidden Valley, Pennsylvania, Jun 24-27","DOI":"10.3115\/116580.116613"},{"key":"9733_CR36","unstructured":"Kingma DP, Ba J (2014) Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980"},{"key":"9733_CR37","doi-asserted-by":"crossref","unstructured":"He K, Lei S, Yang Y, Jiang H, Wang Z (2020) Syntactic graph convolutional network for spoken language understanding. In: Proceedings of the 28th International Conference on Computational Linguistics, pp 2728\u20132738","DOI":"10.18653\/v1\/2020.coling-main.246"},{"key":"9733_CR38","doi-asserted-by":"crossref","unstructured":"Zhang L, Ma D, Zhang X, Yan X, Wang H (2020) Graph lstm with context-gated mechanism for spoken language understanding. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol 34, pp 9539\u20139546","DOI":"10.1609\/aaai.v34i05.6499"},{"key":"9733_CR39","doi-asserted-by":"crossref","unstructured":"Ding Z, Yang Z, Lin H, Wang J (2021) Focus on interaction: a novel dynamic graph model for joint multiple intent detection and slot filling. In: IJCAI, pp 3801\u20133807","DOI":"10.24963\/ijcai.2021\/523"},{"issue":"3","key":"9733_CR40","doi-asserted-by":"publisher","first-page":"2409","DOI":"10.3233\/JIFS-211674","volume":"42","author":"P Wei","year":"2022","unstructured":"Wei P, Zeng B, Liao W (2022) Joint intent detection and slot filling with wheel-graph attention networks. J Intell Fuzzy Syst 42(3):2409\u20132420","journal-title":"J Intell Fuzzy Syst"},{"key":"9733_CR41","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2023.107756","volume":"207","author":"X Hao","year":"2023","unstructured":"Hao X, Wang L, Zhu H, Guo X (2023) Joint agricultural intent detection and slot filling based on enhanced heterogeneous attention mechanism. Comput Electron Agric 207:107756","journal-title":"Comput Electron Agric"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-09733-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-024-09733-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-09733-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,9]],"date-time":"2024-08-09T18:07:03Z","timestamp":1723226823000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-024-09733-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4,22]]},"references-count":41,"journal-issue":{"issue":"22","published-print":{"date-parts":[[2024,8]]}},"alternative-id":["9733"],"URL":"https:\/\/doi.org\/10.1007\/s00521-024-09733-8","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,4,22]]},"assertion":[{"value":"15 April 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 March 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 April 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}