{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T09:13:48Z","timestamp":1782378828255,"version":"3.54.5"},"reference-count":52,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2019,5,2]],"date-time":"2019-05-02T00:00:00Z","timestamp":1556755200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61563040"],"award-info":[{"award-number":["61563040"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61773224"],"award-info":[{"award-number":["61773224"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004763","name":"Natural Science Foundation of Inner Mongolia","doi-asserted-by":"publisher","award":["2016ZD06"],"award-info":[{"award-number":["2016ZD06"]}],"id":[{"id":"10.13039\/501100004763","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Process Lett"],"published-print":{"date-parts":[[2019,12]]},"DOI":"10.1007\/s11063-019-10044-6","type":"journal-article","created":{"date-parts":[[2019,5,2]],"date-time":"2019-05-02T14:04:29Z","timestamp":1556805869000},"page":"2647-2664","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Learning Morpheme Representation for Mongolian Named Entity Recognition"],"prefix":"10.1007","volume":"50","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3234-7151","authenticated-orcid":false,"given":"Weihua","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feilong","family":"Bao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guanglai","family":"Gao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2019,5,2]]},"reference":[{"key":"10044_CR1","doi-asserted-by":"crossref","unstructured":"Abudukelimu H, Liu Y, Chen X, Sun M, Abulizi A (2015) Learning distributed representations of uyghur words and morphemes. In: Chinese computational linguistics and natural language processing based on naturally annotated big data\u201414th China National Conference, CCL 2015 and third international symposium, NLP-NABD 2015, Guangzhou, China, November 13\u201314, 2015, Proceedings, pp 202\u2013211","DOI":"10.1007\/978-3-319-25816-4_17"},{"key":"10044_CR2","doi-asserted-by":"crossref","unstructured":"Arisoy E, Sethy A, Ramabhadran B, Chen SF (2015) Bidirectional recurrent neural network language models for automatic speech recognition. In: 2015 IEEE international conference on acoustics, speech and signal processing, ICASSP 2015, South Brisbane, Queensland, Australia, April 19\u201324, 2015, pp 5421\u20135425","DOI":"10.1109\/ICASSP.2015.7179007"},{"key":"10044_CR3","unstructured":"Benajiba Y, Rosso P (2008) Arabic named entity recognition using conditional random fields. In: Proceedings of workshop on HLT & NLP within the Arabic World, LREC, vol 8, pp 143\u2013153"},{"key":"10044_CR4","unstructured":"Benajiba Y, Zitouni I, Diab M, Rosso P (2010) Arabic named entity recognition: using features extracted from noisy data. In: Proceedings of the ACL 2010 conference short papers, pp 281\u2013285. Association for Computational Linguistics"},{"key":"10044_CR5","first-page":"1137","volume":"3","author":"Y Bengio","year":"2003","unstructured":"Bengio Y, Ducharme R, Vincent P, Janvin C (2003) A neural probabilistic language model. J Mach Learn Res 3:1137\u20131155","journal-title":"J Mach Learn Res"},{"issue":"2","key":"10044_CR6","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1109\/72.279181","volume":"5","author":"Y Bengio","year":"1994","unstructured":"Bengio Y, Simard PY, Frasconi P (1994) Learning long-term dependencies with gradient descent is difficult. IEEE Trans Neural Net 5(2):157\u2013166","journal-title":"IEEE Trans Neural Net"},{"key":"10044_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":"10044_CR8","unstructured":"Botha JA, Blunsom P (2014) Compositional morphology for word representations and language modelling. In: Proceedings of the 31th international conference on machine learning, ICML 2014, Beijing, China, 21\u201326 June 2014, pp 1899\u20131907"},{"key":"10044_CR9","unstructured":"Chen X, Xu L, Liu Z, Sun M, Luan H (2015) Joint learning of character and word embeddings. In: Proceedings of the twenty-fourth international joint conference on artificial intelligence, IJCAI 2015, Buenos Aires, Argentina, July 25\u201331, 2015, pp 1236\u20131242"},{"key":"10044_CR10","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1162\/tacl_a_00104","volume":"4","author":"Jason P.C. Chiu","year":"2016","unstructured":"Chiu J, Nichols E (2016) Named entity recognition with bidirectional lstm-cnns. Trans Assoc Comput Linguist 4:357\u2013370. http:\/\/www.aclweb.org\/anthology\/Q16-1026","journal-title":"Transactions of the Association for Computational Linguistics"},{"key":"10044_CR11","doi-asserted-by":"publisher","unstructured":"Cho K, van Merrienboer B, Gulcehre C, Bahdanau D, Bougares F, Schwenk H, Bengio Y (2014) Learning phrase representations using rnn encoder\u2013decoder for statistical machine translation. In: Proceedings of the 2014 conference on empirical methods in natural language processing, pp 1724\u20131734. Association for Computational Linguistics. https:\/\/doi.org\/10.3115\/v1\/D14-1179 . http:\/\/www.aclweb.org\/anthology\/D14-1179","DOI":"10.3115\/v1\/D14-1179"},{"issue":"Aug","key":"10044_CR12","first-page":"2493","volume":"12","author":"R Collobert","year":"2011","unstructured":"Collobert R, Weston J, Bottou L, Karlen M, Kavukcuoglu K, Kuksa P (2011) Natural language processing (almost) from scratch. J Mach Learn Res 12(Aug):2493\u20132537","journal-title":"J Mach Learn Res"},{"issue":"1","key":"10044_CR13","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1075\/li.30.1.03nad","volume":"30","author":"SS David Nadeau","year":"2007","unstructured":"David Nadeau SS (2007) A survey of named entity recognition and classification. Lingvisticae Investig 30(1):3\u201326","journal-title":"Lingvisticae Investig"},{"key":"10044_CR14","doi-asserted-by":"crossref","unstructured":"Graves A, Mohamed A, Hinton GE (2013) Speech recognition with deep recurrent neural networks. In: IEEE international conference on acoustics, speech and signal processing, ICASSP 2013, Vancouver, BC, Canada, May 26\u201331, 2013, pp 6645\u20136649","DOI":"10.1109\/ICASSP.2013.6638947"},{"issue":"8","key":"10044_CR15","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. https:\/\/doi.org\/10.1162\/neco.1997.9.8.1735","journal-title":"Neural Comput"},{"key":"10044_CR16","unstructured":"Huang EH, Socher R, Manning CD, Ng AY (2012) Improving word representations via global context and multiple word prototypes. In: The 50th annual meeting of the association for computational linguistics, proceedings of the conference, July 8\u201314, 2012, Jeju Island, Korea\u2014Volume 1: Long Papers, pp 873\u2013882"},{"key":"10044_CR17","unstructured":"Huang Z, Xu W, Yu K (2015) Bidirectional LSTM-CRF models for sequence tagging. CoRR arXiv:1508.01991"},{"key":"10044_CR18","doi-asserted-by":"crossref","unstructured":"Irsoy O, Cardie C (2014) Opinion mining with deep recurrent neural networks. In: Proceedings of the 2014 conference on empirical methods in natural language processing, EMNLP 2014, October 25\u201329, 2014, Doha, Qatar, A meeting of SIGDAT, a Special Interest Group of the ACL, pp 720\u2013728","DOI":"10.3115\/v1\/D14-1080"},{"key":"10044_CR19","unstructured":"Kazama J, Torisawa K (2007) Exploiting wikipedia as external knowledge for named entity recognition. In: Proceedings of the 2007 joint conference on empirical methods in natural language processing and computational natural language learning (EMNLP-CoNLL)"},{"key":"10044_CR20","doi-asserted-by":"crossref","unstructured":"Kim Y, Jernite Y, Sontag D, Rush AM (2016) Character-aware neural language models. In: AAAI, pp 2741\u20132749","DOI":"10.1609\/aaai.v30i1.10362"},{"key":"10044_CR21","doi-asserted-by":"crossref","unstructured":"Konkol M, Konop\u00edk M (2013) CRF-based Czech named entity recognizer and consolidation of czech NER research. In: Text, speech, and dialogue, pp 153\u2013160. Springer","DOI":"10.1007\/978-3-642-40585-3_20"},{"key":"10044_CR22","doi-asserted-by":"crossref","unstructured":"Kudo T, Matsumoto Y (2001) Chunking with support vector machines. In: Proceedings of the 2001 conference of the North American chapter of the association for computational linguistics. Association for Computational Linguistics","DOI":"10.3115\/1073336.1073361"},{"key":"10044_CR23","unstructured":"Lafferty J, McCallum A, Pereira FC (2001) Conditional random fields: probabilistic models for segmenting and labeling sequence data"},{"key":"10044_CR24","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 the 2016 conference of the North American chapter of the association for computational linguistics: human language technologies, pp 260\u2013270. Association for Computational Linguistics, San Diego, California","DOI":"10.18653\/v1\/N16-1030"},{"key":"10044_CR25","unstructured":"Liu L, Shang J, Xu F, Ren X, Gui H, Peng J, Han J (2017) Empower sequence labeling with task-aware neural language model. arXiv preprint arXiv:1709.04109"},{"key":"10044_CR26","unstructured":"Luong M, Le QV, Sutskever I, Vinyals O, Kaiser L (2015) Multi-task sequence to sequence learning. CoRR arXiv:1511.06114"},{"key":"10044_CR27","unstructured":"Luong T, Socher R, Manning CD (2013) Better word representations with recursive neural networks for morphology. In: Proceedings of the seventeenth conference on computational natural language learning, CoNLL 2013, Sofia, Bulgaria, August 8\u20139, 2013, pp 104\u2013113"},{"key":"10044_CR28","doi-asserted-by":"publisher","unstructured":"Ma X, Hovy E (2016) End-to-end sequence labeling via bi-directional lstm-cnns-crf. In: Proceedings of the 54th annual meeting of the association for computational linguistics (volume 1: long papers), pp 1064\u20131074. Association for computational linguistics. https:\/\/doi.org\/10.18653\/v1\/P16-1101 . http:\/\/www.aclweb.org\/anthology\/P16-1101","DOI":"10.18653\/v1\/P16-1101"},{"key":"10044_CR29","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 2013, 14th annual conference of the international speech communication association, Lyon, France, August 25\u201329, 2013, pp 3771\u20133775","DOI":"10.21437\/Interspeech.2013-596"},{"key":"10044_CR30","doi-asserted-by":"crossref","unstructured":"Ogawa A, Hori T (2015) ASR error detection and recognition rate estimation using deep bidirectional recurrent neural networks. In: 2015 IEEE international conference on acoustics, speech and signal processing, ICASSP 2015, South Brisbane, Queensland, Australia, April 19\u201324, 2015, pp 4370\u20134374","DOI":"10.1109\/ICASSP.2015.7178796"},{"key":"10044_CR31","doi-asserted-by":"publisher","unstructured":"Peng N, Dredze M (2016) Improving named entity recognition for chinese social media with word segmentation representation learning. In: Proceedings of the 54th annual meeting of the association for computational linguistics (volume 2: short papers), pp 149\u2013155. Association for computational linguistics. https:\/\/doi.org\/10.18653\/v1\/P16-2025 . http:\/\/aclweb.org\/anthology\/P16-2025","DOI":"10.18653\/v1\/P16-2025"},{"key":"10044_CR32","doi-asserted-by":"crossref","unstructured":"Pennington J, Socher R, Manning CD (2014) Glove: global vectors for word representation. In: Empirical methods in natural language processing (EMNLP), pp 1532\u20131543. http:\/\/www.aclweb.org\/anthology\/D14-1162","DOI":"10.3115\/v1\/D14-1162"},{"key":"10044_CR33","doi-asserted-by":"publisher","unstructured":"Plank B, S\u00f8gaard A, Goldberg Y (2016) Multilingual part-of-speech tagging with bidirectional long short-term memory models and auxiliary loss. In: Proceedings of the 54th annual meeting of the association for computational linguistics (volume 2: short papers), pp 412\u2013418. Association for computational linguistics. https:\/\/doi.org\/10.18653\/v1\/P16-2067 . http:\/\/www.aclweb.org\/anthology\/P16-2067","DOI":"10.18653\/v1\/P16-2067"},{"key":"10044_CR34","doi-asserted-by":"crossref","unstructured":"Radford W, Carreras X, Henderson J (2015) Named entity recognition with document-specific KB tag gazetteers. In: Proceedings of the 2015 conference on empirical methods in natural language processing, EMNLP 2015, Lisbon, Portugal, September 17\u201321, 2015, pp 512\u2013517","DOI":"10.18653\/v1\/D15-1058"},{"key":"10044_CR35","doi-asserted-by":"crossref","unstructured":"Ratinov L, Roth D (2009) Design challenges and misconceptions in named entity recognition. In: Proceedings of the thirteenth conference on computational natural language learning (CoNLL-2009), pp 147\u2013155. Association for Computational Linguistics, Boulder, Colorado","DOI":"10.3115\/1596374.1596399"},{"key":"10044_CR36","doi-asserted-by":"publisher","unstructured":"Rei M (2017) Semi-supervised multitask learning for sequence labeling. In: Proceedings of the 55th annual meeting of the association for computational linguistics (volume 1: long papers), pp 2121\u20132130. Association for computational linguistics. https:\/\/doi.org\/10.18653\/v1\/P17-1194 . http:\/\/www.aclweb.org\/anthology\/P17-1194","DOI":"10.18653\/v1\/P17-1194"},{"key":"10044_CR37","unstructured":"Rei M, Crichton G, Pyysalo S (2016) Attending to characters in neural sequence labeling models. In: Proceedings of COLING 2016, the 26th international conference on computational linguistics: technical papers, pp 309\u2013318. The COLING 2016 organizing committee. http:\/\/www.aclweb.org\/anthology\/C16-1030"},{"key":"10044_CR38","doi-asserted-by":"crossref","unstructured":"Reimers N, Gurevych I (2017) Reporting score distributions makes a difference: performance study of LSTM-networks for sequence tagging. In: Proceedings of the 2017 conference on empirical methods in natural language processing, pp 338\u2013348. Association for computational linguistics. http:\/\/aclweb.org\/anthology\/D17-1035","DOI":"10.18653\/v1\/D17-1035"},{"key":"10044_CR39","unstructured":"Sasano R, Kurohashi S (2008) Japanese named entity recognition using structural natural language processing. In: IJCNLP, pp 607\u2013612"},{"key":"10044_CR40","unstructured":"\u015eeker GA, \u015fen Eryi\u011fit G (2012) Initial explorations on using CRFS for Turkish named entity recognition. In: Proceedings of the 24th international conference on computational linguistics, COLING 2012. Mumbai, India"},{"issue":"11","key":"10044_CR41","doi-asserted-by":"publisher","first-page":"2673","DOI":"10.1109\/78.650093","volume":"45","author":"M Schuster","year":"1997","unstructured":"Schuster M, Paliwal KK (1997) Bidirectional recurrent neural networks. IEEE Trans Signal Process 45(11):2673\u20132681","journal-title":"IEEE Trans Signal Process"},{"key":"10044_CR42","doi-asserted-by":"crossref","unstructured":"Seltzer ML, Droppo J (2013) Multi-task learning in deep neural networks for improved phoneme recognition. In: 2013 IEEE international conference on acoustics, speech and signal processing (ICASSP), pp 6965\u20136969. IEEE","DOI":"10.1109\/ICASSP.2013.6639012"},{"key":"10044_CR43","doi-asserted-by":"crossref","unstructured":"Sen S, Mitra M, Bhattacharyya A, Sarkar R, Schwenker F, Roy K (2019) Feature selection for recognition of online handwritten bangla characters. Neural Process Lett 1\u201324","DOI":"10.1007\/s11063-019-10010-2"},{"key":"10044_CR44","doi-asserted-by":"crossref","unstructured":"Wang L, Cao Z, Xia Y, de Melo G (2016) Morphological segmentation with window LSTM neural networks. In: Proceedings of the 13rd AAAI conference on artificial intelligence, pp 2842\u20132848","DOI":"10.1609\/aaai.v30i1.10363"},{"key":"10044_CR45","unstructured":"Wang W, Bao F, Gao G (2015) Mongolian named entity recognition using suffixes segmentation. In: Proceedings of 2015 international conference on asian language processing (IALP), pp 169\u2013172. Suzhou, China"},{"key":"10044_CR46","doi-asserted-by":"crossref","unstructured":"Wang W, Bao F, Gao G (2016) Cyrillic mongolian named entity recognition with rich features. In: Natural language understanding and intelligent applications, pp 497\u2013505. Springer","DOI":"10.1007\/978-3-319-50496-4_42"},{"key":"10044_CR47","unstructured":"Wang W, Bao F, Gao G (2016) Mongolian named entity recognition system with rich features. In: Proceedings of the 26th international conference on computational linguistics (COLING): technical papers, pp 505\u2013512. The COLING 2016 Organizing Committee, Osaka, Japan. http:\/\/www.aclweb.org\/anthology\/C16-1049"},{"key":"10044_CR48","doi-asserted-by":"crossref","unstructured":"Wang Z, Jiang T, Chang B, Sui Z (2015) Chinese semantic role labeling with bidirectional recurrent neural networks. In: Proceedings of the 2015 conference on empirical methods in natural language processing, EMNLP 2015, Lisbon, Portugal, September 17\u201321, 2015, pp 1626\u20131631","DOI":"10.18653\/v1\/D15-1186"},{"key":"10044_CR49","doi-asserted-by":"crossref","unstructured":"Yannakoudakis H, Rei M, Andersen \u00d8E, Yuan Z (2017) Neural sequence-labelling models for grammatical error correction. In: Proceedings of the 2017 conference on empirical methods in natural language processing, pp 2795\u20132806","DOI":"10.18653\/v1\/D17-1297"},{"key":"10044_CR50","doi-asserted-by":"publisher","unstructured":"Yin R, Wang Q, Li P, Li R, Wang B (2016) Multi-granularity chinese word embedding. In: Proceedings of the 2016 conference on empirical methods in natural language processing, pp 981\u2013986. Association for computational linguistics. https:\/\/doi.org\/10.18653\/v1\/D16-1100 . http:\/\/aclweb.org\/anthology\/D16-1100","DOI":"10.18653\/v1\/D16-1100"},{"key":"10044_CR51","first-page":"649","volume-title":"Advances in Neural Information Processing Systems 28","author":"X Zhang","year":"2015","unstructured":"Zhang X, Zhao J, LeCun Y (2015) Character-level convolutional networks for text classification. In: Cortes C, Lawrence ND, Lee DD, Sugiyama M, Garnett R (eds) Advances in Neural Information Processing Systems 28. Curran Associates, Inc., Red Hook, pp 649\u2013657"},{"key":"10044_CR52","doi-asserted-by":"crossref","unstructured":"Zhou G, Su J (2002) Named entity recognition using an HMM-based chunk tagger. In: Proceedings of the 40th annual meeting on association for computational linguistics, pp. 473\u2013480. Association for Computational Linguistics","DOI":"10.3115\/1073083.1073163"}],"container-title":["Neural Processing Letters"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-019-10044-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11063-019-10044-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-019-10044-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,17]],"date-time":"2022-09-17T08:39:06Z","timestamp":1663403946000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11063-019-10044-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,5,2]]},"references-count":52,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2019,12]]}},"alternative-id":["10044"],"URL":"https:\/\/doi.org\/10.1007\/s11063-019-10044-6","relation":{},"ISSN":["1370-4621","1573-773X"],"issn-type":[{"value":"1370-4621","type":"print"},{"value":"1573-773X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,5,2]]},"assertion":[{"value":"2 May 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}