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Named Entity Recognition (NER) performance often degrades rapidly when applied to target domains that differ from the texts observed during training.
Deep probabilistic logic: A unifying framework for indirect supervision
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Domain adaptation with structural correspondence learning
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An effective two-stage model for exploiting non-local dependencies in named entity recognition
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Named entity recognition for question answering
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Biographies, Bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification
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Frustratingly easy domain adaptation
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Domain adaptation with latent semantic association for named entity recognition
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Distant supervision for relation extraction without labeled data
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Design challenges and misconceptions in named entity recognition
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OntoNotes: A large training corpus for enhanced processing
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Marginalized denoising autoencoders for domain adaptation
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Bayesian classifier combination
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Learning whom to trust with MACE
Dirk Hovy, Taylor Berg-Kirkpatrick, Ashish Vaswani, and Eduard Hovy. 2013 · 2013
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Using structured events to predict stock price movement: An empirical investigation
Xiao Ding, Yue Zhang, Ting Liu, and Junwen Duan. 2014 · 2014
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Glove: Global vectors for word representation
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Sequence labeling with multiple annotators
Filipe Rodrigues, Francisco Pereira, and Bernardete Ribeiro. 2014 · 2014
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Dbpedia - a large-scale, multilingual knowledge base extracted from wikipedia
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Domain adaption of named entity recognition to support credit risk assessment
Julio Cesar Salinas Alvarado, Karin Verspoor, and Timothy Baldwin. 2015 · 2015
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Projecting embeddings for domain adaption: Joint modeling of sentiment analysis in diverse domains
Jeremy Barnes, Roman Klinger, and Sabine Schulte im Walde. 2018 · 2018
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Neckar: A named entity classifier for wikidata
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A knowledge-grounded neural conversation model
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Universal language model fine-tuning for text classification
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Deeptype: Multilingual entity linking by neural type system evolution
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Amber Stubbs, Christopher Kotfila, and Özlem Uzuner. 2015 · 2015
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Geonames ontology
Marc Wick. 2015 · 2015
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Named entity recognition with bidirectional LSTM-CNNs
Jason P.C. Chiu and Eric Nichols. 2016 · 2016
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Broad twitter corpus: A diverse named entity recognition resource
Leon Derczynski, Kalina Bontcheva, and Ian Roberts. 2016 · 2016
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Harnessing deep neural networks with logic rules
Zhiting Hu, Xuezhe Ma, Zhengzhong Liu, Eduard Hovy, and Eric Xing. 2016 · 2016
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Neural architectures for named entity recognition
Guillaume Lample, Miguel Ballesteros, Sandeep Subramanian, Kazuya Kawakami, and Chris Dyer. 2016 · 2016
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Results of the WNUT16 named entity recognition shared task
Benjamin Strauss, Bethany Toma, Alan Ritter, Marie-Catherine de Marneffe, and Wei Xu. 2016 · 2016
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Jonathan Raiman and Olivier Raiman. 2018 · 2018
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Ensemble learning: A survey
Omer Sagi and Lior Rokach. 2018 · 2018
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Neural machine translation incorporating named entity
Arata Ugawa, Akihiro Tamura, Takashi Ninomiya, Hiroya Takamura, and Manabu Okumura. 2018 · 2018
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Domain-specific named entity recognition with document-level optimization
Limin Wang, Shoushan Li, Qian Yan, and Guodong Zhou. 2018 · 2018
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A survey on recent advances in named entity recognition from deep learning models
Vikas Yadav and Steven Bethard. 2018 · 2018
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A survey of feature selection methods for Gaussian mixture models and hidden Markov models
Stephen Adams and Peter A Beling. 2019 · 2019
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Pooled contextualized embeddings for named entity recognition
Alan Akbik, Tanja Bergmann, and Roland Vollgraf. 2019 · 2019
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Unsupervised domain adaptation of contextualized embeddings for sequence labeling
Xiaochuang Han and Jacob Eisenstein. 2019 · 2019
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An adaptive simulated annealing EM algorithm for inference on non-homogeneous hidden Markov models
Aliaksandr Hubin. 2019 · 2019
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Snorkel: rapid training data creation with weak supervision
Alexander Ratner, Stephen H. Bach, Henry Ehrenberg, Jason Fries, Sen Wu, and Christopher Ré. 2019 · 2019
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A Bayesian approach for sequence tagging with crowds
Edwin D. Simpson and Iryna Gurevych. 2019 · 2019
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Dual adversarial neural transfer for low-resource named entity recognition
Joey Tianyi Zhou, Hao Zhang, Di Jin, Hongyuan Zhu, Meng Fang, Rick Siow Mong Goh, and Kenneth Kwok. 2019 · 2019
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Weakly supervised sequence tagging from noisy rules
Esteban Safranchik, Shiying Luo, and Stephen H. Bach. 2020 · 2020
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Neural adaptation layers for cross-domain named entity recognition
Bill Yuchen Lin and Wei Lu. 2018 · 2022
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Learning named entity tagger using domain-specific dictionary
Jingbo Shang, Liyuan Liu, Xiaotao Gu, Xiang Ren, Teng Ren, and Jiawei Han. 2018 · 2064
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