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Volumn 2, Issue , 2018, Pages 452-457

Contextual augmentation: Data augmentation bywords with paradigmatic relations

Author keywords

[No Author keywords available]

Indexed keywords

CONVOLUTIONAL NEURAL NETWORKS; LABELED DATA; RECURRENT NEURAL NETWORKS; TEXT PROCESSING;

EID: 85064048320     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (474)

References (38)
  • 1
    • 84965179228 scopus 로고    scopus 로고
    • Scheduled sampling for sequence prediction with recurrent neural networks
    • Samy Bengio, Oriol Vinyals, Navdeep Jaitly, and Noam Shazeer. 2015. Scheduled sampling for sequence prediction with recurrent neural networks. In NIPS, pages 1171-1179.
    • (2015) NIPS , pp. 1171-1179
    • Bengio, S.1    Vinyals, O.2    Jaitly, N.3    Shazeer, N.4
  • 2
    • 85072902617 scopus 로고    scopus 로고
    • Training data augmentation for low-resource morphological inflection
    • Toms Bergmanis, Katharina Kann, Hinrich Schütze, and Sharon Goldwater. 2017. Training data augmentation for low-resource morphological inflection. In CoNLL SIGMORPHON, pages 31-39.
    • (2017) CoNLL SIGMORPHON , pp. 31-39
    • Bergmanis, T.1    Kann, K.2    Schütze, H.3    Goldwater, S.4
  • 3
    • 80053402648 scopus 로고    scopus 로고
    • Semi-supervised semantic role labeling using the latent words language model
    • Koen Deschacht and Marie-Francine Moens. 2009. Semi-supervised semantic role labeling using the latent words language model. In EMNLP, pages 21-29.
    • (2009) EMNLP , pp. 21-29
    • Deschacht, K.1    Moens, M.2
  • 4
    • 84943742882 scopus 로고    scopus 로고
    • Transitionbased dependency parsing with stack long shortterm memory
    • Chris Dyer, Miguel Ballesteros, Wang Ling, Austin Matthews, and Noah A. Smith. 2015. Transitionbased dependency parsing with stack long shortterm memory. In ACL, pages 334-343.
    • (2015) ACL , pp. 334-343
    • Dyer, C.1    Ballesteros, M.2    Ling, W.3    Matthews, A.4    Smith, N.A.5
  • 5
    • 85037344824 scopus 로고    scopus 로고
    • Data augmentation for low-resource neural machine translation
    • Marzieh Fadaee, Arianna Bisazza, and Christof Monz. 2017. Data augmentation for low-resource neural machine translation. In ACL, pages 567-573.
    • (2017) ACL , pp. 567-573
    • Fadaee, M.1    Bisazza, A.2    Monz, C.3
  • 6
    • 85083951345 scopus 로고    scopus 로고
    • MaskGAN: Better text generation via filling in the
    • William Fedus, Ian Goodfellow, and Andrew M. Dai. 2018. MaskGAN: Better text generation via filling in the. In ICLR.
    • (2018) ICLR
    • Fedus, W.1    Goodfellow, I.2    Dai, A.M.3
  • 7
    • 77950793077 scopus 로고    scopus 로고
    • Semisupervised semantic role labeling
    • Hagen Fürstenau and Mirella Lapata. 2009. Semisupervised semantic role labeling. In EACL, pages 220-228.
    • (2009) EACL , pp. 220-228
    • Fürstenau, H.1    Lapata, M.2
  • 10
    • 85041109778 scopus 로고    scopus 로고
    • Toward controlled generation of text
    • Zhiting Hu, Zichao Yang, Xiaodan Liang, Ruslan Salakhutdinov, and Eric P. Xing. 2017. Toward controlled generation of text. In ICML, pages 1587-1596.
    • (2017) ICML , pp. 1587-1596
    • Hu, Z.1    Yang, Z.2    Liang, X.3    Salakhutdinov, R.4    Xing, E.P.5
  • 11
    • 84893681011 scopus 로고    scopus 로고
    • Vocal tract length perturbation (vtlp) improves speech recognition
    • Navdeep Jaitly and Geoffrey E Hinton. 2015. Vocal tract length perturbation (vtlp) improves speech recognition. In ICML.
    • (2015) ICML
    • Jaitly, N.1    Hinton, G.E.2
  • 12
    • 85012023602 scopus 로고    scopus 로고
    • Data recombination for neural semantic parsing
    • Robin Jia and Percy Liang. 2016. Data recombination for neural semantic parsing. In ACL, pages 12-22.
    • (2016) ACL , pp. 12-22
    • Jia, R.1    Liang, P.2
  • 13
    • 85056988096 scopus 로고    scopus 로고
    • Data augmentation for visual question answering
    • Kushal Kafle, Mohammed Yousefhussien, and Christopher Kanan. 2017. Data augmentation for visual question answering. In INLG, pages 198-202.
    • (2017) INLG , pp. 198-202
    • Kafle, K.1    Yousefhussien, M.2    Kanan, C.3
  • 14
    • 84961376850 scopus 로고    scopus 로고
    • Convolutional neural networks for sentence classification
    • Yoon Kim. 2014. Convolutional neural networks for sentence classification. In EMNLP, pages 1746-1751.
    • (2014) EMNLP , pp. 1746-1751
    • Kim, Y.1
  • 15
    • 85072846169 scopus 로고    scopus 로고
    • Sequencelevel knowledge distillation
    • Yoon Kim and Alexander M. Rush. 2016. Sequencelevel knowledge distillation. In EMNLP, pages 1317-1327.
    • (2016) EMNLP , pp. 1317-1327
    • Kim, Y.1    Rush, A.M.2
  • 16
    • 84959118622 scopus 로고    scopus 로고
    • Audio augmentation for speech recognition
    • Tom Ko, Vijayaditya Peddinti, Daniel Povey, and Sanjeev Khudanpur. 2015. Audio augmentation for speech recognition. In INTERSPEECH, pages 3586-3589.
    • (2015) INTERSPEECH , pp. 3586-3589
    • Ko, T.1    Peddinti, V.2    Povey, D.3    Khudanpur, S.4
  • 17
    • 85065647642 scopus 로고    scopus 로고
    • A neural language model for dynamically representing the meanings of unknown words and entities in a discourse
    • Sosuke Kobayashi, Naoaki Okazaki, and Kentaro Inui. 2017. A neural language model for dynamically representing the meanings of unknown words and entities in a discourse. In IJCNLP, pages 473-483.
    • (2017) IJCNLP , pp. 473-483
    • Kobayashi, S.1    Okazaki, N.2    Inui, K.3
  • 18
    • 84994145773 scopus 로고    scopus 로고
    • Dynamic entity representation with max-pooling improves machine reading
    • Sosuke Kobayashi, Ran Tian, Naoaki Okazaki, and Kentaro Inui. 2016. Dynamic entity representation with max-pooling improves machine reading. In Proceedings of NAACL-HLT, pages 850-855.
    • (2016) Proceedings of NAACL-HLT , pp. 850-855
    • Kobayashi, S.1    Tian, R.2    Okazaki, N.3    Inui, K.4
  • 19
    • 84859015028 scopus 로고    scopus 로고
    • Model-portability experiments for textual temporal analysis
    • Oleksandr Kolomiyets, Steven Bethard, and Marie-Francine Moens. 2011. Model-portability experiments for textual temporal analysis. In ACL, pages 271-276.
    • (2011) ACL , pp. 271-276
    • Kolomiyets, O.1    Bethard, S.2    Moens, M.3
  • 20
    • 84876231242 scopus 로고    scopus 로고
    • Imagenet classification with deep convolutional neural networks
    • Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. 2012. Imagenet classification with deep convolutional neural networks. In NIPS, pages 1097-1105.
    • (2012) NIPS , pp. 1097-1105
    • Krizhevsky, A.1    Sutskever, I.2    Hinton, G.E.3
  • 21
    • 1542370072 scopus 로고    scopus 로고
    • Learning question classifiers
    • Xin Li and Dan Roth. 2002. Learning question classifiers. In COLING, pages 1-7.
    • (2002) COLING , pp. 1-7
    • Li, X.1    Roth, D.2
  • 23
    • 84976702763 scopus 로고
    • Wordnet: A lexical database for english
    • George A. Miller. 1995. Wordnet: A lexical database for english. Commun. ACM, 38(11):39-41.
    • (1995) Commun. ACM , vol.38 , Issue.11 , pp. 39-41
    • Miller, G.A.1
  • 24
    • 85141280473 scopus 로고    scopus 로고
    • A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts
    • Bo Pang and Lillian Lee. 2004. A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts. In ACL.
    • (2004) ACL
    • Pang, B.1    Lee, L.2
  • 25
    • 84859895244 scopus 로고    scopus 로고
    • Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales
    • Bo Pang and Lillian Lee. 2005. Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales. In ACL, pages 115-124.
    • (2005) ACL , pp. 115-124
    • Pang, B.1    Lee, L.2
  • 27
    • 85011945222 scopus 로고    scopus 로고
    • Improving neural machine translation models with monolingual data
    • Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016. Improving neural machine translation models with monolingual data. In ACL, pages 86-96.
    • (2016) ACL , pp. 86-96
    • Sennrich, R.1    Haddow, B.2    Birch, A.3
  • 30
    • 84926358845 scopus 로고    scopus 로고
    • Recursive deep models for semantic compositionality over a sentiment treebank
    • Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D. Manning, Andrew Ng, and Christopher Potts. 2013. Recursive deep models for semantic compositionality over a sentiment treebank. In EMNLP, pages 1631-1642.
    • (2013) EMNLP , pp. 1631-1642
    • Socher, R.1    Perelygin, A.2    Wu, J.3    Chuang, J.4    Manning, C.D.5    Ng, A.6    Potts, C.7
  • 31
    • 84928547704 scopus 로고    scopus 로고
    • Sequence to sequence learning with neural networks
    • Ilya Sutskever, Oriol Vinyals, and Quoc V Le. 2014. Sequence to sequence learning with neural networks. In NIPS, pages 3104-3112.
    • (2014) NIPS , pp. 3104-3112
    • Sutskever, I.1    Vinyals, O.2    Le, Q.V.3
  • 34
    • 84959928437 scopus 로고    scopus 로고
    • That's so annoying!!!: A lexical and frame-semantic embedding based data augmentation approach to automatic categorization of annoying behaviors using #petpeeve tweets
    • William Yang Wang and Diyi Yang. 2015. That's so annoying!!!: A lexical and frame-semantic embedding based data augmentation approach to automatic categorization of annoying behaviors using #petpeeve tweets. In EMNLP, pages 2557-2563.
    • (2015) EMNLP , pp. 2557-2563
    • Yang Wang, W.1    Yang, D.2
  • 35
    • 33644632271 scopus 로고    scopus 로고
    • Annotating expressions of opinions and emotions in language
    • Janyce Wiebe, Theresa Wilson, and Claire Cardie. 2005. Annotating expressions of opinions and emotions in language. Language Resources and Evaluation, 39(2):165-210.
    • (2005) Language Resources and Evaluation , vol.39 , Issue.2 , pp. 165-210
    • Wiebe, J.1    Wilson, T.2    Cardie, C.3
  • 36
    • 85060438826 scopus 로고    scopus 로고
    • Dual supervised learning
    • Yingce Xia, Tao Qin, Wei Chen, Jiang Bian, Nenghai Yu, and Tie-Yan Liu. 2017. Dual supervised learning. In ICML, pages 3789-3798.
    • (2017) ICML , pp. 3789-3798
    • Xia, Y.1    Qin, T.2    Chen, W.3    Bian, J.4    Yu, N.5    Liu, T.6
  • 37
    • 85030464344 scopus 로고    scopus 로고
    • Variational autoencoder for semi-supervised text classification
    • Weidi Xu, Haoze Sun, Chao Deng, and Ying Tan. 2017. Variational autoencoder for semi-supervised text classification. In AAAI, pages 3358-3364.
    • (2017) AAAI , pp. 3358-3364
    • Xu, W.1    Sun, H.2    Deng, C.3    Tan, Y.4
  • 38
    • 84965162393 scopus 로고    scopus 로고
    • Character-level convolutional networks for text classification
    • Xiang Zhang, Junbo Zhao, and Yann LeCun. 2015. Character-level convolutional networks for text classification. In NIPS, pages 649-657.
    • (2015) NIPS , pp. 649-657
    • Zhang, X.1    Zhao, J.2    LeCun, Y.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.