{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T20:28:13Z","timestamp":1743020893244,"version":"3.40.3"},"publisher-location":"Cham","reference-count":35,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030630300"},{"type":"electronic","value":"9783030630317"}],"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\/978-3-030-63031-7_11","type":"book-chapter","created":{"date-parts":[[2020,11,12]],"date-time":"2020-11-12T00:05:35Z","timestamp":1605139535000},"page":"144-158","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Chinese Named Entity Recognition via Adaptive Multi-pass Memory Network with Hierarchical Tagging Mechanism"],"prefix":"10.1007","author":[{"given":"Pengfei","family":"Cao","sequence":"first","affiliation":[]},{"given":"Yubo","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Kang","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Jun","family":"Zhao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,11,12]]},"reference":[{"key":"11_CR1","doi-asserted-by":"crossref","unstructured":"Bunescu, R., Mooney, R.: A shortest path dependency kernel for relation extraction. In: Proceedings of EMNLP, pp. 724\u2013731 (2005)","DOI":"10.3115\/1220575.1220666"},{"key":"11_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 EMNLP (2018)","DOI":"10.18653\/v1\/D18-1017"},{"key":"11_CR3","unstructured":"Che, W., Wang, M., Manning, C.D., Liu, T.: Named entity recognition with bilingual constraints. In: Proceedings of NAACL-HLT, pp. 52\u201362 (2013)"},{"key":"11_CR4","unstructured":"Chen, A., Peng, F., Shan, R., Sun, G.: Chinese named entity recognition with conditional probabilistic models. In: Proceedings of the Fifth SIGHAN Workshop on Chinese Language Processing, pp. 213\u2013216 (2006)"},{"key":"11_CR5","doi-asserted-by":"crossref","unstructured":"Chen, Y., Xu, L., Liu, K., Zeng, D., Zhao, J.: Event extraction via dynamic multi-pooling convolutional neural networks. In: Proceedings of ACL, pp. 167\u2013176 (2015)","DOI":"10.3115\/v1\/P15-1017"},{"key":"11_CR6","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":"11_CR7","doi-asserted-by":"crossref","unstructured":"Gui, T., et al.: A lexicon-based graph neural network for Chinese NER. In: EMNLP-IJCNLP (2019)","DOI":"10.18653\/v1\/D19-1096"},{"key":"11_CR8","doi-asserted-by":"crossref","unstructured":"He, H., Sun, X.: F-score driven max margin neural network for named entity recognition in Chinese social media. arXiv preprint arXiv:1611.04234 (2016)","DOI":"10.18653\/v1\/E17-2113"},{"key":"11_CR9","doi-asserted-by":"crossref","unstructured":"He, H., Sun, X.: A unified model for cross-domain and semi-supervised named entity recognition in Chinese social media. In: Proceedings of AAAI (2017)","DOI":"10.1609\/aaai.v31i1.10977"},{"key":"11_CR10","unstructured":"Huang, Z., Xu, W., Yu, K.: Bidirectional LSTM-CRF models for sequence tagging. arXiv preprint arXiv:1508.01991 (2015)"},{"key":"11_CR11","doi-asserted-by":"crossref","unstructured":"Isozaki, H., Kazawa, H.: Efficient support vector classifiers for named entity recognition. In: Proceedings of the 19th International Conference on Computational Linguistics, vol. 1, pp. 1\u20137 (2002)","DOI":"10.3115\/1072228.1072282"},{"key":"11_CR12","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)"},{"key":"11_CR13","unstructured":"Lafferty, J., McCallum, A., Pereira, F.C.: Conditional random fields: probabilistic models for segmenting and labeling sequence data (2001)"},{"key":"11_CR14","doi-asserted-by":"crossref","unstructured":"Lample, G., Ballesteros, M., Subramanian, S., Kawakami, K., Dyer, C.: Neural architectures for named entity recognition. In: Proceedings of NAACL-HLT, pp. 260\u2013270 (2016)","DOI":"10.18653\/v1\/N16-1030"},{"key":"11_CR15","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":"11_CR16","unstructured":"Lu, Y., Zhang, Y., Ji, D.H.: Multi-prototype Chinese character embedding. In: Proceedings of LREC (2016)"},{"key":"11_CR17","doi-asserted-by":"crossref","unstructured":"Luo, F., Liu, T., Xia, Q., Chang, B., Sui, Z.: Incorporating glosses into neural word sense disambiguation. In: Proceedings of ACL, pp. 2473\u20132482 (2018)","DOI":"10.18653\/v1\/P18-1230"},{"key":"11_CR18","doi-asserted-by":"crossref","unstructured":"Ma, X., Hovy, E.: End-to-end sequence labeling via bi-directional LSTM-CNNs-CRF. In: Proceedings of ACL, pp. 1064\u20131074 (2016)","DOI":"10.18653\/v1\/P16-1101"},{"key":"11_CR19","unstructured":"Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781 (2013)"},{"key":"11_CR20","doi-asserted-by":"crossref","unstructured":"Peng, N., Dredze, M.: Named entity recognition for Chinese social media with jointly trained embeddings. In: Proceedings of EMNLP, pp. 548\u2013554 (2015)","DOI":"10.18653\/v1\/D15-1064"},{"key":"11_CR21","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 ACL, pp. 149\u2013155 (2016)","DOI":"10.18653\/v1\/P16-2025"},{"key":"11_CR22","doi-asserted-by":"crossref","unstructured":"Peters, M., Ammar, W., Bhagavatula, C., Power, R.: Semi-supervised sequence tagging with bidirectional language models. In: Proceedings of ACL, pp. 1756\u20131765 (2017)","DOI":"10.18653\/v1\/P17-1161"},{"key":"11_CR23","doi-asserted-by":"crossref","unstructured":"Sui, D., Chen, Y., Liu, K., Zhao, J., Liu, S.: Leverage lexical knowledge for Chinese named entity recognition via collaborative graph network. In: EMNLP-IJCNLP (2019)","DOI":"10.18653\/v1\/D19-1396"},{"key":"11_CR24","unstructured":"Sukhbaatar, S., Weston, J., Fergus, R., et al.: End-to-end memory networks. In: Proceedings of NeurIPS, pp. 2440\u20132448 (2015)"},{"key":"11_CR25","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.1998.712192","volume-title":"Introduction to reinforcement learning","author":"RS Sutton","year":"1998","unstructured":"Sutton, R.S., Barto, A.G., et al.: Introduction to reinforcement learning. MIT Press, Cambridge (1998)"},{"key":"11_CR26","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 AAAI (2013)","DOI":"10.1609\/aaai.v27i1.8617"},{"key":"11_CR27","unstructured":"Weischedel, R., et al.: OntoNotes release 4.0. LDC2011T03, Philadelphia, Penn.: Linguistic Data Consortium (2011)"},{"key":"11_CR28","doi-asserted-by":"crossref","unstructured":"Yahya, M., Berberich, K., Elbassuoni, S., Weikum, G.: Robust question answering over the web of linked data. In: Proceedings of CIKM, pp. 1107\u20131116 (2013)","DOI":"10.1145\/2505515.2505677"},{"key":"11_CR29","doi-asserted-by":"crossref","unstructured":"Yang, J., Teng, Z., Zhang, M., Zhang, Y.: Combining discrete and neural features for sequence labeling. In: International Conference on Intelligent Text Processing and Computational Linguistics, pp. 140\u2013154 (2016)","DOI":"10.1007\/978-3-319-75477-2_9"},{"key":"11_CR30","doi-asserted-by":"crossref","unstructured":"Yang, Z., Yang, D., Dyer, C., He, X., Smola, A., Hovy, E.: Hierarchical attention networks for document classification. In: Proceedings of NAACL-HLT, pp. 1480\u20131489 (2016)","DOI":"10.18653\/v1\/N16-1174"},{"key":"11_CR31","unstructured":"Zhang, S., Qin, Y., Wen, 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":"11_CR32","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Chen, H., Zhao, Y., Liu, Q., Yin, D.: Learning tag dependencies for sequence tagging. In: Proceedings of IJCAI, pp. 4581\u20134587 (2018)","DOI":"10.24963\/ijcai.2018\/637"},{"key":"11_CR33","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Yang, J.: Chinese NER using lattice LSTM. In: Proceedings of ACL, pp. 1554\u20131564 (2018)","DOI":"10.18653\/v1\/P18-1144"},{"key":"11_CR34","unstructured":"Zhou, J., He, L., Dai, X., Chen, J.: Chinese named entity recognition with a multi-phase model. In: Proceedings of the Fifth SIGHAN Workshop on Chinese Language Processing (2006)"},{"key":"11_CR35","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, 225\u2013230 (2013)","journal-title":"Chin. J. Electron."}],"container-title":["Lecture Notes in Computer Science","Chinese Computational Linguistics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-63031-7_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T19:01:45Z","timestamp":1710270105000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-63031-7_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030630300","9783030630317"],"references-count":35,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-63031-7_11","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":"12 November 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CCL","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China National Conference on Chinese Computational Linguistics","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hainan","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":"30 October 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1 November 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cncl2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.cips-cl.org\/static\/CCL2020\/index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"www.softconf.com","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"99","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":"32","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":"2","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":"32% - 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":"3","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)"}}]}}