Negation and speculation scope detection using recursive neural conditional random fields

Neurocomputing - Tập 374 - Trang 22-29 - 2020
Hao Fei1, Yafeng Ren2, Donghong Ji1
1School of Cyber Science and Engineering, Wuhan University, Wuhan, China
2Collaborative Innovation Center for Language Research and Service, Guangdong University of Foreign Studies, Guangzhou, China

Tài liệu tham khảo

Özgür, 2009, Detecting speculations and their scopes in scientific text, 1398 Øvrelid, 2010, Syntactic scope resolution in uncertainty analysis, 1379 Tang, 2010, A cascade method for detecting hedges and their scope in natural language text, 13 Zou, 2013, Tree kernel-based negation and speculation scope detection with structured syntactic parse features, 968 Qian, 2016, Speculation and negation scope detection via convolutional neural networks, 815 Fancellu, 2016, Neural networks for negation scope detection, 495 Socher, 2011, Parsing natural scenes and natural language with recursive neural networks, 129 Socher, 2013, Recursive deep models for semantic compositionality over a sentiment treebank, 1631 Socher, 2014, Grounded compositional semantics for finding and describing images with sentences, Trans. Assoc. Comput. Linguist., 2, 207, 10.1162/tacl_a_00177 Iyyer, 2014, A neural network for factoid question answering over paragraphs, 633 Xu, 2016, Dependency-based gated recursive neural network for chinese word segmentation, 2, 567 Mac Kim, 2017, Demographic inference on twitter using recursive neural networks, 2, 471 Chapman, 2001, Evaluation of negation phrases in narrative clinical reports Goldin, 2003, Learning to detect negation with “not” in medical texts Huang, 2007, A novel hybrid approach to automated negation detection in clinical radiology reports, J. Am. Med. Inf. Assoc., 14, 304, 10.1197/jamia.M2284 Apostolova, 2011, Automatic extraction of lexico-syntactic patterns for detection of negation and speculation scopes, 283 Ballesteros, 2012, UCM-2: a rule-based approach to infer the scope of negation via dependency parsing, 288 Vincze, 2008, The bioscope corpus: biomedical texts annotated for uncertainty, negation and their scopes, BMC Bioinf., 9, 1 Morante, 2008, Learning the scope of negation in biomedical texts, 715 Morante, 2009, Learning the scope of hedge cues in biomedical texts, 28 Velldal, 2012, Speculation and negation: rules, rankers, and the role of syntax, Comput. Linguist., 38, 369, 10.1162/COLI_a_00126 Lapponi, 2012, UIO 2: sequence-labeling negation using dependency features, 319 Yao, 2018, Identification method for a class of periodic discrete-time dynamic nonlinear systems based on sinusoidal esn, Neurocomputing, 275, 1511, 10.1016/j.neucom.2017.09.092 Ren, 2019, A hybrid neural network model for predicting kidney disease in hypertension patients based on electronic health records, BMC Med. Inform. Decis. Mak., 19, 51, 10.1186/s12911-019-0765-4 Yao, 2019, Prediction and identification of discrete-time dynamic nonlinear systems based on adaptive echo state network, Neural Netw., 113, 11, 10.1016/j.neunet.2019.01.003 Ren, 2016, Context-sensitive twitter sentiment classification using neural network., 215 Xu, 2016, Exponential stability of almost periodic solutions for memristor-based neural networks with distributed leakage delays, Neural Comput., 28, 2726, 10.1162/NECO_a_00895 Xu, 2017, Global exponential convergence of neutral-type hopfield neural networks with multi-proportional delays and leakage delays, Chaos Solitons Fractals, 96, 139, 10.1016/j.chaos.2017.01.012 Chen, 2017, Long short-term memory RNN for biomedical named entity recognition, BMC Bioinf., 18, 462, 10.1186/s12859-017-1868-5 Xu, 2018, Global exponential convergence of fuzzy cellular neural networks with leakage delays, distributed delays and proportional delays, Circuits Syst. Signal Process., 37, 163, 10.1007/s00034-017-0557-y Xu, 2018, Local and global hopf bifurcation analysis on simplified bidirectional associative memory neural networks with multiple delays, Math. Comput. Simul., 149, 69, 10.1016/j.matcom.2018.02.002 Xu, 2018, On anti-periodic solutions for neutral shunting inhibitory cellular neural networks with time-varying delays and d operator, Neurocomputing, 275, 377, 10.1016/j.neucom.2017.08.030 Ren, 2018, Context-augmented convolutional neural networks for twitter sarcasm detection, Neurocomputing, 308, 1, 10.1016/j.neucom.2018.03.047 Fancellu, 2018, Neural networks for cross-lingual negation scope detection, CoRR Fabregat, 2019 Ren, 2018, Detecting the scope of negation and speculation in biomedical texts by using recursive neural network, 739 Morante, 2012, * sem 2012 shared task: resolving the scope and focus of negation, 265 Lafferty, 2001, Conditional random fields: probabilistic models for segmenting and labeling sequence data, 282 Zou, 2015, Negation and speculation identification in chinese language, 1, 656 Manning, 2014, The stanford CoreNLP natural language processing toolkit, 55 Zhang, 2008, A tale of two parsers: investigating and combining graph-based and transition-based dependency parsing using beam-search, 562 Yamada, 2003, Statistical dependency analysis with support vector machines, 195