{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T06:16:34Z","timestamp":1743142594768,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":21,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819947515"},{"type":"electronic","value":"9789819947522"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-981-99-4752-2_55","type":"book-chapter","created":{"date-parts":[[2023,7,30]],"date-time":"2023-07-30T16:02:10Z","timestamp":1690732930000},"page":"670-681","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Chinese Named Entity Recognition Based on Multi-feature Fusion"],"prefix":"10.1007","author":[{"given":"Zhenxiang","family":"Sun","sequence":"first","affiliation":[]},{"given":"Runyuan","family":"Sun","sequence":"additional","affiliation":[]},{"given":"Zhifeng","family":"Liang","sequence":"additional","affiliation":[]},{"given":"Zhuang","family":"Su","sequence":"additional","affiliation":[]},{"given":"Yongxin","family":"Yu","sequence":"additional","affiliation":[]},{"given":"Shuainan","family":"Wu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,7,31]]},"reference":[{"unstructured":"Kenton, J.D.M.W.C., Toutanova, L.K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of naacL-HLT, vol. 1, p. 2 (2019)","key":"55_CR1"},{"unstructured":"Yang, Z., Dai, Z., Yang, Y., Carbonell, J., Salakhutdinov, R.R., Le, Q.V.: Xlnet: generalized autoregressive pretraining for language understanding. In: Advances in Neural Information Processing Systems, vol. 32 (2019)","key":"55_CR2"},{"doi-asserted-by":"crossref","unstructured":"Collobert, R., Weston, J.: A unified architecture for natural language processing: deep neural networks with multitask learning. In: Proceedings of the 25th International Conference on Machine Learning, pp. 160\u2013167 (2008)","key":"55_CR3","DOI":"10.1145\/1390156.1390177"},{"key":"55_CR4","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1162\/tacl_a_00104","volume":"4","author":"JP Chiu","year":"2016","unstructured":"Chiu, J.P., Nichols, E.: Named entity recognition with bidirectional LSTM-CNNs. Trans. Assoc. Comput. Linguist. 4, 357\u2013370 (2016)","journal-title":"Trans. Assoc. Comput. Linguist."},{"unstructured":"Lewis, P., et al.: Retrieval-augmented generation for knowledge-intensive NLP tasks. In: Advances in Neural Information Processing Systems, vol. 33, pp. 9459\u20139474 (2020)","key":"55_CR5"},{"doi-asserted-by":"crossref","unstructured":"Lample, G., Ballesteros, M., Subramanian, S., Kawakami, K., Dyer, C.: Neural architectures for named entity recognition. arXiv preprint arXiv:1603.01360 (2016)","key":"55_CR6","DOI":"10.18653\/v1\/N16-1030"},{"doi-asserted-by":"crossref","unstructured":"Ma, X., Hovy, E.: End-to-end sequence labeling via bi-directional LSTM-CNNs-CRF. arXiv preprint arXiv:1603.01354 (2016)","key":"55_CR7","DOI":"10.18653\/v1\/P16-1101"},{"unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, vol. 30 (2017)","key":"55_CR8"},{"unstructured":"Cui, Y., et al.: A span-extraction dataset for Chinese machine reading comprehension. arXiv preprint arXiv:1810.07366 (2018)","key":"55_CR9"},{"unstructured":"Sun, Y., et al.: Ernie: enhanced representation through knowledge integration. arXiv preprint arXiv:1904.09223 (2019)","key":"55_CR10"},{"doi-asserted-by":"crossref","unstructured":"Sun, Z., et al.: ChineseBERT: Chinese pretraining enhanced by glyph and pinyin information. arXiv preprint arXiv:2106.16038 (2021)","key":"55_CR11","DOI":"10.18653\/v1\/2021.acl-long.161"},{"doi-asserted-by":"crossref","unstructured":"Yang, J., Wang, H., Tang, Y., Yang, F.: Incorporating lexicon and character glyph and morphological features into BiLSTM-CRF for Chinese medical NER. In: 2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE), pp. 12\u201317. IEEE (2021)","key":"55_CR12","DOI":"10.1109\/ICCECE51280.2021.9342121"},{"unstructured":"Li, J., Meng, K.: MFE-NER: multi-feature fusion embedding for Chinese named entity recognition. arXiv preprint arXiv:2109.07877 (2021)","key":"55_CR13"},{"doi-asserted-by":"crossref","unstructured":"Chen, C., Kong, F.: Enhancing entity boundary detection for better Chinese named entity recognition. In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers), pp. 20\u201325 (2021)","key":"55_CR14","DOI":"10.18653\/v1\/2021.acl-short.4"},{"doi-asserted-by":"crossref","unstructured":"Liu, W., Fu, X., Zhang, Y., Iao, W.: Lexicon enhanced Chinese sequence labeling using BERT adapter. arXiv preprint arXiv:2105.07148 (2021)","key":"55_CR15","DOI":"10.18653\/v1\/2021.acl-long.454"},{"unstructured":"Geng, Z., Yan, H., Yin, Z., An, C., Qiu, X.: Turner: the uncertainty-based retrieval framework for Chinese NER. arXiv preprint arXiv:2202.09022 (2022)","key":"55_CR16"},{"unstructured":"Zheng, L., Ren, L.: Named entity recognition in the domain of nutrition and health using fusion rules and BERT-flflat model. Trans. Chin. Soc. Agric. Eng. 37(20) (2021)","key":"55_CR17"},{"issue":"S2","key":"55_CR18","first-page":"335","volume":"51","author":"X Guo","year":"2020","unstructured":"Guo, X., Tang, Z., Diao, L., Zhou, H., Li, L.: Named entity recognition of pests and diseases based on radical insertion and attention mechanism. J. Agric. Mach. 51(S2), 335\u2013343 (2020)","journal-title":"J. Agric. Mach."},{"unstructured":"Wu, S., Song, X., Feng, Z., Wu, X.: Nflflat: non-flat-lattice transformer for Chinese named entity recognition. arXiv preprint arXiv:2205.05832 (2022)","key":"55_CR19"},{"doi-asserted-by":"crossref","unstructured":"Zhang, Y., Yang, J.: Chinese NER using lattice LSTM. arXiv preprint arXiv:1805.02023 (2018)","key":"55_CR20","DOI":"10.18653\/v1\/P18-1144"},{"unstructured":"Levow, G.A.: The third international Chinese language processing bakeoffff: word segmentation and named entity recognition. In: Proceedings of the Fifth SIGHAN Workshop on Chinese Language Processing, pp. 108\u2013117 (2006)","key":"55_CR21"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-99-4752-2_55","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,1]],"date-time":"2023-08-01T23:16:02Z","timestamp":1690931762000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-99-4752-2_55"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9789819947515","9789819947522"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-981-99-4752-2_55","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"31 July 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Zhengzhou","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":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 August 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 August 2023","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":"icic2023a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2023\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}