{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T19:09:58Z","timestamp":1743102598055,"version":"3.40.3"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030863821"},{"type":"electronic","value":"9783030863838"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-86383-8_28","type":"book-chapter","created":{"date-parts":[[2021,9,10]],"date-time":"2021-09-10T08:02:49Z","timestamp":1631260969000},"page":"345-356","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Hierarchical Lexicon Embedding Architecture for Chinese Named Entity Recognition"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5012-6790","authenticated-orcid":false,"given":"Jiahao","family":"Hu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3329-3906","authenticated-orcid":false,"given":"Yuanxin","family":"Ouyang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7508-7222","authenticated-orcid":false,"given":"Chen","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8888-8387","authenticated-orcid":false,"given":"Chuanrui","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4229-7215","authenticated-orcid":false,"given":"Wenge","family":"Rong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9421-1014","authenticated-orcid":false,"given":"Zhang","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,9,7]]},"reference":[{"key":"28_CR1","unstructured":"Aliod, D.M., van Zaanen, M., Smith, D.: Named entity recognition for question answering. In: Proceedings of the 2006 Australasian Language Technology Workshop, pp. 51\u201358 (2006)"},{"key":"28_CR2","doi-asserted-by":"crossref","unstructured":"Babych, B., Hartley, A.: Improving machine translation quality with automatic named entity recognition. In: Proceedings of the 7th International EAMT workshop on MT and Other Language Technology Tools, Improving MT through other Language Technology Tools, Resource and Tools for Building MT (2003)","DOI":"10.3115\/1609822.1609823"},{"key":"28_CR3","doi-asserted-by":"crossref","unstructured":"Cao, P., Chen, Y., Liu, K., Zhao, J., Liu, S.: Adversarial transfer learning for Chinese named entity recognition with self-attention mechanism. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 182\u2013192 (2018)","DOI":"10.18653\/v1\/D18-1017"},{"key":"28_CR4","unstructured":"Che, W., Wang, M., Manning, C.D., Liu, T.: Named entity recognition with bilingual constraints. In: Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 52\u201362 (2013)"},{"key":"28_CR5","doi-asserted-by":"crossref","unstructured":"Ding, R., Xie, P., Zhang, X., Lu, W., Li, L., Si, L.: A neural multi-digraph model for Chinese NER with gazetteers. In: Proceedings of the 57th Conference of the Association for Computational Linguistics, pp. 1462\u20131467 (2019)","DOI":"10.18653\/v1\/P19-1141"},{"issue":"1","key":"28_CR6","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1016\/j.artint.2005.03.001","volume":"165","author":"O Etzioni","year":"2005","unstructured":"Etzioni, O., et al.: Unsupervised named-entity extraction from the web: an experimental study. Artif. Intell. 165(1), 91\u2013134 (2005)","journal-title":"Artif. Intell."},{"issue":"3","key":"28_CR7","doi-asserted-by":"publisher","first-page":"268","DOI":"10.1109\/PROC.1973.9030","volume":"61","author":"GD Forney","year":"1973","unstructured":"Forney, G.D.: The Viterbi algorithm. Proc. IEEE 61(3), 268\u2013278 (1973)","journal-title":"Proc. IEEE"},{"key":"28_CR8","doi-asserted-by":"crossref","unstructured":"Gui, T., et al.: A lexicon-based graph neural network for Chinese NER. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, pp. 1040\u20131050 (2019)","DOI":"10.18653\/v1\/D19-1096"},{"key":"28_CR9","unstructured":"He, J., Wang, H.: Chinese named entity recognition and word segmentation based on character. In: Proceedings of the 3rd International Joint Conference on Natural Language Processing, pp. 128\u2013132 (2008)"},{"key":"28_CR10","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. In: Proceedings of 3rd International Conference on Learning Representations (2015)"},{"key":"28_CR11","doi-asserted-by":"crossref","unstructured":"Lample, G., Ballesteros, M., Subramanian, S., Kawakami, K., Dyer, C.: 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 (2016)","DOI":"10.18653\/v1\/N16-1030"},{"key":"28_CR12","unstructured":"Levow, G.: The third international chinese language processing bakeoff: word segmentation and named entity recognition. In: Proceedings of the 5th Workshop on Chinese Language Processing, pp. 108\u2013117 (2006)"},{"key":"28_CR13","unstructured":"Li, H., Hagiwara, M., Li, Q., Ji, H.: Comparison of the impact of word segmentation on name tagging for Chinese and Japanese. In: Proceedings of the 9th International Conference on Language Resources and Evaluation, pp. 2532\u20132536 (2014)"},{"key":"28_CR14","doi-asserted-by":"crossref","unstructured":"Li, X., Yan, H., Qiu, X., Huang, X.: FLAT: Chinese NER using flat-lattice transformer. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 6836\u20136842 (2020)","DOI":"10.18653\/v1\/2020.acl-main.611"},{"key":"28_CR15","doi-asserted-by":"crossref","unstructured":"Liu, L., et al.: Empower sequence labeling with task-aware neural language model. In: Proceedings of the 32nd AAAI Conference on Artificial Intelligence, pp. 5253\u20135260 (2018)","DOI":"10.1609\/aaai.v32i1.12006"},{"key":"28_CR16","doi-asserted-by":"crossref","unstructured":"Liu, W., Xu, T., Xu, Q., Song, J., Zu, Y.: An encoding strategy based word-character LSTM for Chinese NER. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 2379\u20132389 (2019)","DOI":"10.18653\/v1\/N19-1247"},{"key":"28_CR17","doi-asserted-by":"crossref","unstructured":"Ma, R., Peng, M., Zhang, Q., Wei, Z., Huang, X.: Simplify the usage of lexicon in Chinese NER. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 5951\u20135960 (2020)","DOI":"10.18653\/v1\/2020.acl-main.528"},{"issue":"1","key":"28_CR18","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1075\/li.30.1.03nad","volume":"30","author":"D Nadeau","year":"2007","unstructured":"Nadeau, D., Sekine, S.: A survey of named entity recognition and classification. Lingvisticae Investigationes 30(1), 3\u201326 (2007)","journal-title":"Lingvisticae Investigationes"},{"key":"28_CR19","doi-asserted-by":"crossref","unstructured":"Peng, N., Dredze, M.: Named entity recognition for Chinese social media with jointly trained embeddings. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pp. 548\u2013554 (2015)","DOI":"10.18653\/v1\/D15-1064"},{"key":"28_CR20","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Proceedings of 2017 Annual Conference on Neural Information Processing Systems, pp. 5998\u20136008 (2017)"},{"key":"28_CR21","doi-asserted-by":"crossref","unstructured":"Wang, M., Che, W., Manning, C.D.: Effective bilingual constraints for semi-supervised learning of named entity recognizers. In: Proceedings of the 27th AAAI Conference on Artificial Intelligence, pp. 919\u2013925 (2013)","DOI":"10.1609\/aaai.v27i1.8617"},{"issue":"1","key":"28_CR22","first-page":"29","volume":"8","author":"N Xu","year":"2003","unstructured":"Xu, N.: Chinese word segmentation as character tagging. Int. J. Comput. Linguist. Chin. Lang. Process. 8(1), 29\u201348 (2003)","journal-title":"Int. J. Comput. Linguist. Chin. Lang. Process."},{"key":"28_CR23","doi-asserted-by":"crossref","unstructured":"Yang, J., Teng, Z., Zhang, M., Zhang, Y.: Combining discrete and neural features for sequence labeling. In: Proceedings of 17th International Conference on Computational Linguistics and Intelligent Text Processing, pp. 140\u2013154 (2016)","DOI":"10.1007\/978-3-319-75477-2_9"},{"key":"28_CR24","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Yang, J.: Chinese NER using lattice LSTM. In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, pp. 1554\u20131564 (2018)","DOI":"10.18653\/v1\/P18-1144"}],"container-title":["Lecture Notes in Computer Science","Artificial Neural Networks and Machine Learning \u2013 ICANN 2021"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-86383-8_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T14:44:48Z","timestamp":1709822688000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-86383-8_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030863821","9783030863838"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-86383-8_28","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"7 September 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICANN","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Neural Networks","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bratislava","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Slovakia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 September 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 September 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icann2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/e-nns.org\/icann2021\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"OCS","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"496","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"265","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"53% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.5","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Conference was held online due to the COVID-19 pandemic.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}