{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T12:39:18Z","timestamp":1763642358557,"version":"3.41.0"},"publisher-location":"Cham","reference-count":65,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319754765"},{"type":"electronic","value":"9783319754772"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"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":[[2018]]},"DOI":"10.1007\/978-3-319-75477-2_9","type":"book-chapter","created":{"date-parts":[[2018,3,20]],"date-time":"2018-03-20T08:53:16Z","timestamp":1521535996000},"page":"140-154","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Combining Discrete and Neural Features for Sequence Labeling"],"prefix":"10.1007","author":[{"given":"Jie","family":"Yang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiyang","family":"Teng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Meishan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yue","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,3,21]]},"reference":[{"key":"9_CR1","unstructured":"Socher, R., Lin, C.C., Manning, C., Ng, A.Y.: Parsing natural scenes and natural language with recursive neural networks. In: ICML, pp. 129\u2013136 (2011)"},{"key":"9_CR2","doi-asserted-by":"crossref","unstructured":"Chen, D., Manning, C.D.: A fast and accurate dependency parser using neural networks. In: EMNLP, vol. 1, pp. 740\u2013750 (2014)","DOI":"10.3115\/v1\/D14-1082"},{"key":"9_CR3","doi-asserted-by":"crossref","unstructured":"Weiss, D., Alberti, C., Collins, M., Petrov, S.: Structured training for neural network transition-based parsing. In: ACL-IJCNLP, pp. 323\u2013333 (2015)","DOI":"10.3115\/v1\/P15-1032"},{"key":"9_CR4","doi-asserted-by":"crossref","unstructured":"Dyer, C., Ballesteros, M., Ling, W., Matthews, A., Smith, N.A.: Transition-based dependency parsing with stack long short-term memory. In: ACL-IJCNLP, pp. 334\u2013343 (2015)","DOI":"10.3115\/v1\/P15-1033"},{"key":"9_CR5","doi-asserted-by":"crossref","unstructured":"Zhou, H., Zhang, Y., Chen, J.: A neural probabilistic structured-prediction model for transition-based dependency parsing. In: ACL, pp. 1213\u20131222 (2015)","DOI":"10.3115\/v1\/P15-1117"},{"key":"9_CR6","doi-asserted-by":"crossref","unstructured":"Durrett, G., Klein, D.: Neural CRF parsing. In: ACL-IJCNLP, pp. 302\u2013312 (2015)","DOI":"10.3115\/v1\/P15-1030"},{"key":"9_CR7","doi-asserted-by":"crossref","unstructured":"Ballesteros, M., Carreras, X.: Transition-based spinal parsing. In: CoNLL (2015)","DOI":"10.18653\/v1\/K15-1029"},{"key":"9_CR8","doi-asserted-by":"crossref","unstructured":"Kalchbrenner, N., Blunsom, P.: Recurrent continuous translation models. In: EMNLP, pp. 1700\u20131709 (2013)","DOI":"10.18653\/v1\/D13-1176"},{"key":"9_CR9","doi-asserted-by":"crossref","unstructured":"Cho, K., Van Merri\u00ebnboer, B., Gulcehre, C., Bahdanau, D., Bougares, F., Schwenk, H., Bengio, Y.: Learning phrase representations using rnn encoder-decoder for statistical machine translation. arXiv preprint arXiv:1406.1078 (2014)","DOI":"10.3115\/v1\/D14-1179"},{"key":"9_CR10","unstructured":"Sutskever, I., Vinyals, O., Le, Q.V.: Sequence to sequence learning with neural networks. In: NIPS, pp. 3104\u20133112 (2014)"},{"key":"9_CR11","unstructured":"Bahdanau, D., Cho, K., Bengio, Y.: Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473 (2015)"},{"key":"9_CR12","unstructured":"Ling, W., Trancoso, I., Dyer, C., Black, A.W.: Character-based neural machine translation. arXiv preprint arXiv:1511.04586 (2015)"},{"key":"9_CR13","doi-asserted-by":"crossref","unstructured":"Jean, S., Cho, K., Memisevic, R., Bengio, Y.: On using very large target vocabulary for neural machine translation. In: ACL-IJCNLP, pp. 1\u201310 (2015)","DOI":"10.3115\/v1\/P15-1001"},{"key":"9_CR14","doi-asserted-by":"crossref","unstructured":"Socher, R., Perelygin, A., Wu, J.Y., Chuang, J., Manning, C.D., Ng, A.Y., Potts, C.: Recursive deep models for semantic compositionality over a sentiment treebank. In: EMNLP, vol. 1631, p. 1642 (2013)","DOI":"10.18653\/v1\/D13-1170"},{"key":"9_CR15","doi-asserted-by":"crossref","unstructured":"Tang, D., Wei, F., Yang, N., Zhou, M., Liu, T., Qin, B.: Learning sentiment-specific word embedding for twitter sentiment classification. In: ACL, vol. 1, pp. 1555\u20131565 (2014)","DOI":"10.3115\/v1\/P14-1146"},{"key":"9_CR16","unstructured":"Nogueira dos Santos, C., Gatti, M.: Deep convolutional neural networks for sentiment analysis of short texts. In: COLING (2014)"},{"key":"9_CR17","unstructured":"Vo, D.-T., Zhang, Y.: Target-dependent twitter sentiment classification with rich automatic features. In: IJCAI, pp. 1347\u20131353 (2015)"},{"key":"9_CR18","doi-asserted-by":"crossref","unstructured":"Zhang, M., Zhang, Y., Vo, D.-T.: Neural networks for open domain targeted sentiment. In: EMNLP (2015)","DOI":"10.18653\/v1\/D15-1073"},{"key":"9_CR19","unstructured":"Socher, R., Chen, D., Manning, C.D., Ng, A.: Reasoning with neural tensor networks for knowledge base completion. In: NIPS, pp. 926\u2013934 (2013)"},{"key":"9_CR20","unstructured":"Wang, M., Manning, C.D.: Effect of non-linear deep architecture in sequence labeling. In: IJCNLP (2013)"},{"key":"9_CR21","unstructured":"Ding, X., Zhang, Y., Liu, T., Duan, J.: Deep learning for event-driven stock prediction. In: ICJAI, pp. 2327\u20132333 (2015)"},{"key":"9_CR22","unstructured":"Mark, G.-W., Stephen, C.: What happens next? event prediction using a compositional neural network. In: AAAI (2016)"},{"key":"9_CR23","unstructured":"Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781 (2013)"},{"key":"9_CR24","doi-asserted-by":"crossref","unstructured":"Pennington, J., Socher, R., Manning, C.D.: Glove: global vectors for word representation. In: EMNLP, vol. 12, pp. 1532\u20131543 (2014)","DOI":"10.3115\/v1\/D14-1162"},{"key":"9_CR25","unstructured":"Collobert, R., Weston, J., Bottou, L., Karlen, M., Kavukcuoglu, K., Kuksa, P.: Natural language processing (almost) from scratch. JMLR 12, 2493\u20132537 (2011)"},{"key":"9_CR26","unstructured":"Turian, J., Ratinov, L., Bengio, Y.: Word representations: a simple and general method for semi-supervised learning. In: ACL, pp. 384\u2013394 (2010)"},{"key":"9_CR27","unstructured":"Lafferty, J., McCallum, A., Pereira, F.C.N.: Probabilistic models for segmenting and labeling sequence data, Conditional random fields (2001)"},{"key":"9_CR28","doi-asserted-by":"crossref","unstructured":"Guo, J., Che, W., Wang, H., Liu, T.: Revisiting embedding features for simple semi-supervised learning. In: EMNLP, pp. 110\u2013120 (2014)","DOI":"10.3115\/v1\/D14-1012"},{"key":"9_CR29","doi-asserted-by":"crossref","unstructured":"Ma, J., Zhang, Y., Zhu, J.: Tagging the web: building a robust web tagger with neural network. In: ACL, vol. 1, pp. 144\u2013154 (2014)","DOI":"10.3115\/v1\/P14-1014"},{"key":"9_CR30","unstructured":"Wang, M., Manning, C.D.: Learning a product of experts with elitist lasso. In: IJCNLP (2013)"},{"key":"9_CR31","doi-asserted-by":"crossref","unstructured":"Zhang, M., Zhang, Y.: Combining discrete and continuous features for deterministic transition-based dependency parsing. In: EMNLP, pp. 1316\u20131321 (2015)","DOI":"10.18653\/v1\/D15-1153"},{"issue":"8","key":"9_CR32","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9(8), 1735\u20131780 (1997)","journal-title":"Neural Comput."},{"issue":"1","key":"9_CR33","first-page":"29","volume":"8","author":"N Xue","year":"2003","unstructured":"Xue, N., et al.: Chinese word segmentation as character tagging. Comput. Linguist. Chin. Lang. Process. 8(1), 29\u201348 (2003)","journal-title":"Comput. Linguist. Chin. Lang. Process."},{"key":"9_CR34","doi-asserted-by":"crossref","unstructured":"Peng, F., Feng, F., McCallum, A.: Chinese segmentation and new word detection using conditional random fields. In: Coling, p. 562 (2004)","DOI":"10.3115\/1220355.1220436"},{"key":"9_CR35","doi-asserted-by":"crossref","unstructured":"Zhao, H.: Character-level dependencies in Chinese: usefulness and learning. In: EACL, pp. 879\u2013887 (2009)","DOI":"10.3115\/1609067.1609165"},{"key":"9_CR36","doi-asserted-by":"crossref","unstructured":"Jiang, W., Huang, L., Liu, Q., L\u00fc, Y.: A cascaded linear model for joint chinese word segmentation and part-of-speech tagging. In: ACL (2008)","DOI":"10.3115\/1599081.1599130"},{"key":"9_CR37","unstructured":"Sun, W.: A stacked sub-word model for joint Chinese word segmentation and part-of-speech tagging. In: HLT-ACL, pp. 1385\u20131394 (2011)"},{"key":"9_CR38","doi-asserted-by":"crossref","unstructured":"Liu, Y., Zhang, Y., Che, W., Liu, T., Wu, F.: Domain adaptation for CRF-based chinese word segmentation using free annotations. In: EMNLP, pp. 864\u2013874 (2014)","DOI":"10.3115\/v1\/D14-1093"},{"key":"9_CR39","doi-asserted-by":"crossref","unstructured":"Zheng, X., Chen, H., Xu, T.: Deep learning for Chinese word segmentation and pos tagging. In: EMNLP, pp. 647\u2013657 (2013)","DOI":"10.18653\/v1\/D13-1061"},{"key":"9_CR40","doi-asserted-by":"crossref","unstructured":"Pei, W., Ge, T., Baobao, C.: Maxmargin tensor neural network for Chinese word segmentation. In: ACL (2014)","DOI":"10.3115\/v1\/P14-1028"},{"key":"9_CR41","doi-asserted-by":"crossref","unstructured":"Chen, X., Qiu, X., Zhu, C., Huang, X.: Gated recursive neural network for Chinese word segmentation. In: EMNLP (2015)","DOI":"10.3115\/v1\/P15-1168"},{"key":"9_CR42","unstructured":"Zhang, Y., Clark, S.: Chinese segmentation with a word-based perceptron algorithm. In: ACL, vol. 45, p. 840 (2007)"},{"key":"9_CR43","unstructured":"Sun, W.: Word-based and character-based word segmentation models: comparison and combination. In: Coling, pp. 1211\u20131219 (2010)"},{"key":"9_CR44","unstructured":"Liu, Y., Zhang, Y.: Unsupervised domain adaptation for joint segmentation and pos-tagging. In: COLING (Posters), pp. 745\u2013754 (2012)"},{"key":"9_CR45","unstructured":"Ratnaparkhi, A., et al.: A maximum entropy model for part-of-speech tagging. In: EMNLP, vol. 1, pp. 133\u2013142 (1996)"},{"key":"9_CR46","doi-asserted-by":"crossref","unstructured":"Collins, M.: Discriminative training methods for hidden Markov models: theory and experiments with perceptron algorithms. In: EMNLP, pp. 1\u20138 (2002)","DOI":"10.3115\/1118693.1118694"},{"key":"9_CR47","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1007\/978-3-642-19400-9_14","volume-title":"Computational Linguistics and Intelligent Text Processing","author":"CD Manning","year":"2011","unstructured":"Manning, C.D.: Part-of-speech tagging from 97% to 100%: is it time for some linguistics? In: Gelbukh, A.F. (ed.) CICLing 2011. LNCS, vol. 6608, pp. 171\u2013189. Springer, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-19400-9_14"},{"key":"9_CR48","unstructured":"Santos, C.D., Zadrozny, B.: Learning character-level representations for part-of-speech tagging. In: ICML, pp. 1818\u20131826 (2014)"},{"key":"9_CR49","doi-asserted-by":"crossref","unstructured":"Perez-Ortiz, J.A., Forcada, M.L.: Part-of-speech tagging with recurrent neural networks. Universitat d\u2019Alacant, Spain (2001)","DOI":"10.1109\/IJCNN.2001.938396"},{"key":"9_CR50","unstructured":"Huang, Z., Xu, W., Yu, K.: Bidirectional LSTM-CRF models for sequence tagging, August 2015"},{"key":"9_CR51","doi-asserted-by":"crossref","unstructured":"McCallum, A., Li, W.: Early results for named entity recognition with conditional random fields, feature induction and web-enhanced lexicons. In: HLT-NAACL, pp. 188\u2013191 (2003)","DOI":"10.3115\/1119176.1119206"},{"key":"9_CR52","doi-asserted-by":"crossref","unstructured":"Leong, C.H., Tou, N.H.: Named entity recognition with a maximum entropy approach. In: HLT-NAACL, vol. 4, pp. 160\u2013163 (2003)","DOI":"10.3115\/1119176.1119199"},{"key":"9_CR53","doi-asserted-by":"crossref","unstructured":"Krishnan, V., Manning, C.D.: An effective two-stage model for exploiting non-local dependencies in named entity recognition. In: Coling and ACL, pp. 1121\u20131128 (2006)","DOI":"10.3115\/1220175.1220316"},{"key":"9_CR54","unstructured":"Che, W., Wang, M., Manning, C.D., Liu, T.: Named entity recognition with bilingual constraints. In: HLT-NAACL, pp. 52\u201362 (2013)"},{"key":"9_CR55","doi-asserted-by":"crossref","unstructured":"Ratinov, L., Roth, D.: Design challenges and misconceptions in named entity recognition. In: Coling, pp. 147\u2013155 (2009)","DOI":"10.3115\/1596374.1596399"},{"key":"9_CR56","doi-asserted-by":"crossref","unstructured":"dos Santos, C., Guimaraes, V., Niter\u00f3i, R.J., de Janeiro, R.: Boosting named entity recognition with neural character embeddings. In: NEWS (2015)","DOI":"10.18653\/v1\/W15-3904"},{"key":"9_CR57","doi-asserted-by":"crossref","unstructured":"Hammerton, J.: Named entity recognition with long short-term memory. In: Daelemans, W., Osborne, M. (eds.) CoNLL, pp. 172\u2013175 (2003)","DOI":"10.3115\/1119176.1119202"},{"key":"9_CR58","doi-asserted-by":"crossref","unstructured":"Chiu, J.P.C., Nichols, E.: Named entity recognition with bidirectional lstm-cnns. arXiv preprint arXiv:1511.08308 (2015)","DOI":"10.1162\/tacl_a_00104"},{"key":"9_CR59","first-page":"2121","volume":"12","author":"Y Singer","year":"2011","unstructured":"Singer, Y., Duchi, J., Hazan, E.: Adaptive subgradient methods for online learning and stochastic optimization. JMLR 12, 2121\u20132159 (2011)","journal-title":"JMLR"},{"issue":"1","key":"9_CR60","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1162\/coli_a_00037","volume":"37","author":"Y Zhang","year":"2011","unstructured":"Zhang, Y., Clark, S.: Syntactic processing using the generalized perceptron and beam search. Comput. Linguist. 37(1), 105\u2013151 (2011)","journal-title":"Comput. Linguist."},{"issue":"1","key":"9_CR61","first-page":"1929","volume":"15","author":"N Srivastava","year":"2014","unstructured":"Srivastava, N., Hinton, G., Krizhevsky, A., Sutskever, I., Salakhutdinov, R.: Dropout: a simple way to prevent neural networks from overfitting. JMLR 15(1), 1929\u20131958 (2014)","journal-title":"JMLR"},{"key":"9_CR62","doi-asserted-by":"crossref","unstructured":"Chen, X., Qiu, X., Zhu, C., Liu, P., Huang, X.: Long short-term memory neural networks for Chinese word segmentation. In: EMNLP, Lisbon, Portugal, pp. 1197\u20131206 (2015)","DOI":"10.18653\/v1\/D15-1141"},{"key":"9_CR63","doi-asserted-by":"crossref","unstructured":"Zhang, M., Zhang, Y., Che, W., Liu, T.: Character-level chinese dependency parsing. In: ACL (2014)","DOI":"10.3115\/v1\/P14-1125"},{"key":"9_CR64","doi-asserted-by":"crossref","unstructured":"Toutanova, K., Klein, D., Manning, C.D., Singer, Y.: Feature-rich part-of-speech tagging with a cyclic dependency network. In: NAACL, pp. 173\u2013180 (2003)","DOI":"10.3115\/1073445.1073478"},{"key":"9_CR65","doi-asserted-by":"crossref","unstructured":"Li, Z., Chao, J., Zhang, M., Chen, W.: Coupled sequence labeling on heterogeneous annotations: Pos tagging as a case study. In: ACL-IJCNLP, pp. 1783\u20131792 (2015)","DOI":"10.3115\/v1\/P15-1172"}],"container-title":["Lecture Notes in Computer Science","Computational Linguistics and Intelligent Text Processing"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-75477-2_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,2]],"date-time":"2025-07-02T21:55:14Z","timestamp":1751493314000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-75477-2_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319754765","9783319754772"],"references-count":65,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-75477-2_9","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]}}}