{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T08:29:09Z","timestamp":1743150549638,"version":"3.40.3"},"publisher-location":"Cham","reference-count":23,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030590154"},{"type":"electronic","value":"9783030590161"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-59016-1_17","type":"book-chapter","created":{"date-parts":[[2020,9,10]],"date-time":"2020-09-10T13:05:10Z","timestamp":1599743110000},"page":"194-205","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["SDTCNs: A Symmetric Double Temporal Convolutional Network for Chinese NER"],"prefix":"10.1007","author":[{"given":"Wei","family":"Jiang","sequence":"first","affiliation":[]},{"given":"Yuan","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Yan","family":"Tang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,9,10]]},"reference":[{"key":"17_CR1","unstructured":"Bai, S., Kolter, J.Z., Koltun, V.: An empirical evaluation of generic convolutional and recurrent networks for sequence modeling. arXiv preprint arXiv:1803.01271 (2018)"},{"key":"17_CR2","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":"17_CR3","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":"17_CR4","unstructured":"Collobert, R., Weston, J., Bottou, L., Karlen, M., Kavukcuoglu, K., Kuksa, P.: Natural language processing (almost) from scratch. J. Mach. Learn. Res. 12(Aug), 2493\u20132537 (2011)"},{"key":"17_CR5","unstructured":"Consortium, L.D., et al.: Ontonotes release 4.0 (2011). https:\/\/catalog.ldc.upenn.edu\/LDC2011T03"},{"key":"17_CR6","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: Bert: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)"},{"key":"17_CR7","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1007\/978-3-319-50496-4_20","volume-title":"Natural Language Understanding and Intelligent Applications","author":"C Dong","year":"2016","unstructured":"Dong, C., Zhang, J., Zong, C., Hattori, M., Di, H.: Character-based LSTM-CRF with radical-level features for Chinese named entity recognition. In: Lin, C.-Y., Xue, N., Zhao, D., Huang, X., Feng, Y. (eds.) ICCPOL\/NLPCC -2016. LNCS (LNAI), vol. 10102, pp. 239\u2013250. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-50496-4_20"},{"key":"17_CR8","doi-asserted-by":"crossref","unstructured":"Grishman, R., Sundheim, B.: Message understanding conference-6: a brief history. In: COLING 1996 Volume 1: The 16th International Conference on Computational Linguistics (1996)","DOI":"10.3115\/992628.992709"},{"key":"17_CR9","doi-asserted-by":"publisher","unstructured":"Gui, T., Ma, R., Zhang, Q., Zhao, L., Jiang, Y.G., Huang, X.: CNN-based Chinese NER with lexicon rethinking. In: Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI-19, pp. 4982\u20134988. International Joint Conferences on Artificial Intelligence Organization, July 2019. https:\/\/doi.org\/10.24963\/ijcai.2019\/692","DOI":"10.24963\/ijcai.2019\/692"},{"key":"17_CR10","doi-asserted-by":"crossref","unstructured":"Hammerton, J.: Named entity recognition with long short-term memory. In: Proceedings of the Seventh Conference on Natural Language Learning at HLT-NAACL 2003, vol. 4, pp. 172\u2013175. Association for Computational Linguistics (2003)","DOI":"10.3115\/1119176.1119202"},{"key":"17_CR11","doi-asserted-by":"crossref","unstructured":"He, H., Sun, X.: F-score driven max margin neural network for named entity recognition in Chinese social media. In: EACL 2017, p. 713 (2017)","DOI":"10.18653\/v1\/E17-2113"},{"key":"17_CR12","unstructured":"Hendrycks, D., Gimpel, K.: Gaussian error linear units (GELUs). arXiv preprint arXiv:1606.08415 (2016)"},{"key":"17_CR13","unstructured":"Levow, G.A.: The third international Chinese language processing bakeoff: word segmentation and named entity recognition. In: Proceedings of the Fifth SIGHAN Workshop on Chinese Language Processing, pp. 108\u2013117 (2006)"},{"key":"17_CR14","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, (Long and Short Papers), vol. 1, pp. 2379\u20132389 (2019)","DOI":"10.18653\/v1\/N19-1247"},{"key":"17_CR15","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":"17_CR16","doi-asserted-by":"crossref","unstructured":"Peng, N., Dredze, M.: 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 (Short Papers), vol. 2, pp. 149\u2013155 (2016)","DOI":"10.18653\/v1\/P16-2025"},{"key":"17_CR17","doi-asserted-by":"crossref","unstructured":"Rau, L.F.: Extracting company names from text. In: [1991] Proceedings of the Seventh IEEE Conference on Artificial Intelligence Application, vol. 1, pp. 29\u201332. IEEE (1991)","DOI":"10.1109\/CAIA.1991.120841"},{"key":"17_CR18","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, pp. 5998\u20136008 (2017)"},{"key":"17_CR19","doi-asserted-by":"crossref","unstructured":"Wang, M., Che, W., Manning, C.D.: Effective bilingual constraints for semi-supervised learning of named entity recognizers. In: Twenty-Seventh AAAI Conference on Artificial Intelligence (2013)","DOI":"10.1609\/aaai.v27i1.8617"},{"key":"17_CR20","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1007\/978-3-319-75477-2_9","volume-title":"Computational Linguistics and Intelligent Text Processing","author":"J Yang","year":"2018","unstructured":"Yang, J., Teng, Z., Zhang, M., Zhang, Y.: Combining discrete and neural features for sequence labeling. In: Gelbukh, A. (ed.) CICLing 2016. LNCS, vol. 9623, pp. 140\u2013154. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-75477-2_9"},{"key":"17_CR21","unstructured":"Zhang, S., Qin, Y., Hou, W.J., Wang, X.: Word segmentation and named entity recognition for SIGHAN bakeoff3. In: Proceedings of the Fifth SIGHAN Workshop on Chinese Language Processing, pp. 158\u2013161 (2006)"},{"key":"17_CR22","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 (Long Papers), vol. 1, pp. 1554\u20131564 (2018)","DOI":"10.18653\/v1\/P18-1144"},{"issue":"2","key":"17_CR23","first-page":"225","volume":"22","author":"J Zhou","year":"2013","unstructured":"Zhou, J., Qu, W., Zhang, F.: Chinese named entity recognition via joint identification and categorization. Chin. J. Electron. 22(2), 225\u2013230 (2013)","journal-title":"Chin. J. Electron."}],"container-title":["Lecture Notes in Computer Science","Wireless Algorithms, Systems, and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-59016-1_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,13]],"date-time":"2024-08-13T15:15:32Z","timestamp":1723562132000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-59016-1_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030590154","9783030590161"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-59016-1_17","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"10 September 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"WASA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Wireless Algorithms, Systems, and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Qingdao","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 September 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 September 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"wasa2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/wasa-conference.org\/WASA2020\/","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":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"216","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":"67","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":"14","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":"31% - 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":"6-7","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":"The conference was held virtually 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)"}}]}}