{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,26]],"date-time":"2025-10-26T22:53:20Z","timestamp":1761519200848,"version":"3.40.3"},"publisher-location":"Cham","reference-count":33,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319690049"},{"type":"electronic","value":"9783319690056"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"unspecified","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":[[2017]]},"DOI":"10.1007\/978-3-319-69005-6_17","type":"book-chapter","created":{"date-parts":[[2017,10,6]],"date-time":"2017-10-06T09:17:45Z","timestamp":1507281465000},"page":"197-208","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Multichannel LSTM-CRF for Named Entity Recognition in Chinese Social Media"],"prefix":"10.1007","author":[{"given":"Chuanhai","family":"Dong","sequence":"first","affiliation":[]},{"given":"Huijia","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Jiajun","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Chengqing","family":"Zong","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,10,7]]},"reference":[{"key":"17_CR1","doi-asserted-by":"crossref","unstructured":"Blitzer, J., McDonald, R., Pereira, F.: Domain adaptation with structural correspondence learning. In: Proceedings of the 2006 conference on empirical methods in natural language processing, pp. 120\u2013128. Association for Computational Linguistics (2006)","DOI":"10.3115\/1610075.1610094"},{"key":"17_CR2","doi-asserted-by":"crossref","unstructured":"Chang, C.Y., Teng, Z., Zhang, Y.: Expectation-regulated neural model for event mention extraction. In: Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 400\u2013410. Association for Computational Linguistics, San Diego, California, June 2016","DOI":"10.18653\/v1\/N16-1045"},{"key":"17_CR3","unstructured":"Chen, Y., Zong, C., Su, K.Y.: On jointly recognizing and aligning bilingual named entities. In: Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, pp. 631\u2013639. Association for Computational Linguistics (2010)"},{"key":"17_CR4","doi-asserted-by":"crossref","unstructured":"Cherry, C., Guo, H.: The unreasonable effectiveness of word representations for twitter named entity recognition. In: HLT-NAACL, pp. 735\u2013745 (2015)","DOI":"10.3115\/v1\/N15-1075"},{"key":"17_CR5","unstructured":"Chiu, J.P., Nichols, E.: Named entity recognition with bidirectional lstm-cnns. arXiv preprint (2015). arXiv:1511.08308"},{"issue":"Aug","key":"17_CR6","first-page":"2493","volume":"12","author":"R Collobert","year":"2011","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)","journal-title":"J. Mach. Learn. Res."},{"key":"17_CR7","unstructured":"Daum\u00e9 III., H.: Frustratingly easy domain adaptation. arXiv preprint (2009). arXiv:0907.1815"},{"key":"17_CR8","unstructured":"Daum\u00e9 III., H., Kumar, A., Saha, A.: Frustratingly easy semi-supervised domain adaptation. In: Proceedings of the 2010 Workshop on Domain Adaptation for Natural Language Processing, pp. 53\u201359. Association for Computational Linguistics (2010)"},{"key":"17_CR9","series-title":"Lecture Notes in Computer Science","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, vol. 10102, pp. 239\u2013250. Springer, Cham (2016). doi: 10.1007\/978-3-319-50496-4_20"},{"key":"17_CR10","unstructured":"Dredze, M., McNamee, P., Rao, D., Gerber, A., Finin, T.: Entity disambiguation for knowledge base population. In: Proceedings of the 23rd International Conference on Computational Linguistics, pp. 277\u2013285. Association for Computational Linguistics (2010)"},{"key":"17_CR11","unstructured":"Dyer, C., Ballesteros, M., Ling, W., Matthews, A., Smith, N.A.: Transition-based dependency parsing with stack long short-term memory. arXiv preprint (2015). arXiv:1505.08075"},{"issue":"1","key":"17_CR12","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1145\/1089815.1089819","volume":"7","author":"G Fu","year":"2005","unstructured":"Fu, G., Luke, K.K.: Chinese named entity recognition using lexicalized hmms. ACM SIGKDD Explor. Newslett. 7(1), 19\u201325 (2005)","journal-title":"ACM SIGKDD Explor. Newslett."},{"key":"17_CR13","unstructured":"Gottipati, S., Jiang, J.: Linking entities to a knowledge base with query expansion. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp. 804\u2013813. Association for Computational Linguistics (2011)"},{"key":"17_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1007\/978-3-642-38634-3_8","volume-title":"Language Processing and Intelligent Information Systems","author":"AL-F Han","year":"2013","unstructured":"Han, A.L.-F., Wong, D.F., Chao, L.S.: Chinese Named Entity Recognition with Conditional Random Fields in the Light of Chinese Characteristics. In: K\u0142opotek, M.A., Koronacki, J., Marciniak, M., Mykowiecka, A., Wierzcho\u0144, S.T. (eds.) IIS 2013. LNCS, vol. 7912, pp. 57\u201368. Springer, Heidelberg (2013). doi: 10.1007\/978-3-642-38634-3_8"},{"key":"17_CR15","unstructured":"He, H., Sun, X.: F-score driven max margin neural network for named entity recognition in chinese social media. arXiv preprint (2016). arXiv:1611.04234"},{"key":"17_CR16","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: Thirty-First AAAI Conference on Artificial Intelligence (2017)","DOI":"10.1609\/aaai.v31i1.10977"},{"key":"17_CR17","unstructured":"Hinton, G.E., Srivastava, N., Krizhevsky, A., Sutskever, I., Salakhutdinov, R.R.: Improving neural networks by preventing co-adaptation of feature detectors. arXiv preprint (2012). arXiv:1207.0580"},{"key":"17_CR18","unstructured":"Huang, Z., Xu, W., Yu, K.: Bidirectional lstm-crf models for sequence tagging. arXiv preprint (2015). arXiv:1508.01991"},{"key":"17_CR19","unstructured":"Kim, Y.B., Stratos, K., Sarikaya, R.: Frustratingly easy neural domain adaptation. In: Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers. The COLING 2016 Organizing Committee, Osaka, Japan, pp. 387\u2013396, December 2016"},{"key":"17_CR20","unstructured":"Lample, G., Ballesteros, M., Subramanian, S., Kawakami, K., Dyer, C.: Neural architectures for named entity recognition. arXiv preprint (2016). arXiv:1603.01360"},{"key":"17_CR21","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_CR22","unstructured":"Li, L., Mao, T., Huang, D., Yang, Y.: Hybrid models for chinese named entity recognition. In: COLING $$\\bullet $$ ACL 2006, p. 72 (2006)"},{"key":"17_CR23","unstructured":"Ma, X., Hovy, E.: End-to-end sequence labeling via bi-directional lstm-cnns-crf. arXiv preprint (2016). arXiv:1603.01354"},{"key":"17_CR24","unstructured":"Mikolov, T., Sutskever, I., Chen, K., Corrado, G.S., Dean, J.: Distributed representations of words and phrases and their compositionality. In: Advances in neural information processing systems, pp. 3111\u20133119 (2013)"},{"issue":"10","key":"17_CR25","doi-asserted-by":"crossref","first-page":"1345","DOI":"10.1109\/TKDE.2009.191","volume":"22","author":"SJ Pan","year":"2010","unstructured":"Pan, S.J., Yang, Q.: A survey on transfer learning. IEEE Trans. Knowl. Data Eng. 22(10), 1345\u20131359 (2010)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"17_CR26","doi-asserted-by":"crossref","unstructured":"Peng, N., Dredze, M.: Named entity recognition for chinese social media with jointly trained embeddings. In: EMNLP, pp. 548\u2013554 (2015)","DOI":"10.18653\/v1\/D15-1064"},{"key":"17_CR27","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, vol. 2, pp. 149\u2013155 (2016)","DOI":"10.18653\/v1\/P16-2025"},{"key":"17_CR28","unstructured":"Peng, N., Dredze, M.: Multi-task multi-domain representation learning for sequence tagging. arXiv preprint (2016). arXiv:1608.02689"},{"key":"17_CR29","doi-asserted-by":"crossref","unstructured":"Ratinov, L., Roth, D.: Design challenges and misconceptions in named entity recognition. In: Proceedings of the Thirteenth Conference on Computational Natural Language Learning, pp. 147\u2013155. Association for Computational Linguistics (2009)","DOI":"10.3115\/1596374.1596399"},{"key":"17_CR30","unstructured":"Rehurek, R., Sojka, P.: Software framework for topic modelling with large corpora. In: Proceedings of the LREC 2010 Workshop on New Challenges for NLP Frameworks. Citeseer (2010)"},{"key":"17_CR31","unstructured":"Ritter, A., Clark, S., Etzioni, O., et al.: Named entity recognition in tweets: an experimental study. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp. 1524\u20131534. Association for Computational Linguistics (2011)"},{"issue":"1","key":"17_CR32","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40537-016-0043-6","volume":"3","author":"K Weiss","year":"2016","unstructured":"Weiss, K., Khoshgoftaar, T.M., Wang, D.: A survey of transfer learning. J. Big Data 3(1), 1\u201340 (2016)","journal-title":"J. Big Data"},{"key":"17_CR33","unstructured":"Yang, Z., Salakhutdinov, R., Cohen, W.W.: Transfer learning for sequence tagging with hierarchical recurrent networks. arXiv preprint (2017). arXiv:1703.06345"}],"container-title":["Lecture Notes in Computer Science","Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-69005-6_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,4]],"date-time":"2022-08-04T01:49:06Z","timestamp":1659577746000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-69005-6_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9783319690049","9783319690056"],"references-count":33,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-69005-6_17","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2017]]}}}