Convolutional neural network for paraphrase identification

NAACL HLT 2015 - 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference

Volumn , Issue , 2015, Pages 901-911

  Yin, Wenpeng ^a   Schütze, Hinrich ^a  

^a UNIVERSITY OF MUNICH   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTATIONAL LINGUISTICS; CONVOLUTION; DEEP LEARNING; NEURAL NETWORKS;

CONVOLUTIONAL NEURAL NETWORK; LANGUAGE MODEL; LEARNING ARCHITECTURES; MODEL INTERACTION; MULTIPLE LEVELS; PARAPHRASE IDENTIFICATIONS; TRAINING DATA;

MODELING LANGUAGES;

EID: 84959908091     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3115/v1/n15-1091     Document Type: Conference Paper

References (35)

1. Ngo Xuan Bach, Nguyen Le Minh, and Akira Shimazu. 2014. Exploiting discourse information to identify paraphrases. Expert Systems with Applications, 41(6):2832-2841.
2. Yoshua Bengio, Réjean Ducharme, Pascal Vincent, and Christian Jauvin. 2003. A neural probabilistic language model. Journal of Machine Learning Research, 3:1137-1155.
3. William Blacoe and Mirella Lapata. 2012. A comparison of vector-based representations for semantic composition. In Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, pages 546-556.
4. David M Blei, Andrew Y Ng, and Michael I Jordan. 2003. Latent dirichlet allocation. the Journal of machine Learning research, 3:993-1022.
5. Jane Bromley, James W Bentz, Léon Bottou, Isabelle Guyon, Yann LeCun, Cliff Moore, Eduard Säckinger, and Roopak Shah. 1993. Signature verification using a "siamese" time delay neural network. International Journal of Pattern Recognition and Artificial Intelligence, 7(04):669-688.
6. Yee Seng Chan and Hwee Tou Ng. 2008. Maxsim: A maximum similarity metric for machine translation evaluation. In ACL, pages 55-62.
7. Ronan Collobert and Jason Weston. 2008. A unified architecture for natural language processing: Deep neural networks with multitask learning. In Proceedings of the 25th international conference on Machine learning, pages 160-167.
8. Dipanjan Das and Noah A Smith. 2009. Paraphrase identification as probabilistic quasi-synchronous recognition. In Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1-Volume 1, pages 468-476.
9. Li Deng, Geoffrey Hinton, and Brian Kingsbury. 2013. New types of deep neural network learning for speech recognition and related applications: An overview. In Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on, pages 8599-8603.
10. Michael Denkowski and Alon Lavie. 2010. Extending the meteor machine translation evaluation metric to the phrase level. In Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, pages 250-253.
11. George Doddington. 2002. Automatic evaluation of machine translation quality using n-gram co-occurrence statistics. In Proceedings of the second international conference on Human Language Technology Research, pages 138-145.
12. Bill Dolan, Chris Quirk, and Chris Brockett. 2004. Unsupervised construction of large paraphrase corpora: Exploiting massively parallel news sources. In Proceedings of the 20th international conference on Computational Linguistics, page 350.
13. John Duchi, Elad Hazan, and Yoram Singer. 2011. Adaptive subgradient methods for online learning and stochastic optimization. The Journal of Machine Learning Research, 12:2121-2159.
14. Jianfeng Gao, Patrick Pantel, Michael Gamon, Xiaodong He, Li Deng, and Yelong Shen. 2014. Modeling interestingness with deep neural networks. In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing.
15. David Graff, Junbo Kong, Ke Chen, and Kazuaki Maeda. 2003. English gigaword. Linguistic Data Consortium, Philadelphia.
16. Nizar Habash and Ahmed Elkholy. 2008. Sepia: surface span extension to syntactic dependency precisionbased mt evaluation. In Proceedings of the NIST metrics for machine translation workshop at the association for machine translation in the Americas conference, AMTA-2008. Waikiki, HI.
17. Baotian Hu, Zhengdong Lu, Hang Li, and Qingcai Chen. 2014. Convolutional neural network architectures for matching natural language sentences. In Advances in Neural Information Processing Systems.
18. Yangfeng Ji and Jacob Eisenstein. 2013. Discriminative improvements to distributional sentence similarity. In Proceedings of the Conference on Empirical Methods in Natural Language Processing.
19. Nal Kalchbrenner, Edward Grefenstette, and Phil Blunsom. 2014. A convolutional neural network for modelling sentences. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics.
20. Quoc V Le and Tomas Mikolov. 2014. Distributed representations of sentences and documents. In Proceedings of the 31th international conference on Machine learning.
21. Zhengdong Lu and Hang Li. 2013. A deep architecture for matching short texts. In Advances in Neural Information Processing Systems, pages 1367-1375.
22. Nitin Madnani, Joel Tetreault, and Martin Chodorow. 2012. Re-examining machine translation metrics for paraphrase identification. In Proceedings of the 2012 NAACL-HLT, pages 182-190.
23. Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013. Efficient estimation of word representations in vector space. In Proceedings of Workshop at Tomáš Mikolov. 2012. Statistical language models based on neural networks. Ph.D. thesis, Ph. D. thesis, Brno University of Technology.
24. Andriy Mnih and Koray Kavukcuoglu. 2013. Learning word embeddings efficiently with noise-contrastive estimation. In Advances in Neural Information Processing Systems, pages 2265-2273.
25. Andriy Mnih and Yee Whye Teh. 2012. A fast and simple algorithm for training neural probabilistic language models. In Proceedings of the 29th International Conference on Machine Learning, pages 1751-1758.
26. N Neverova, C Wolf, GW Taylor, and F Nebout. 2014. Multi-scale deep learning for gesture detection and localization. In European Conference on Computer Vision (ECCV) 2014 ChaLearn Workshop. Zurich.
27. Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002. Bleu: a method for automatic evaluation of machine translation. In Proceedings of the 40th ACL, pages 311-318.
28. Steven Parker. 2008. Badger: A new machine translation metric. Metrics for Machine Translation Challenge.
29. Matthew Snover, Bonnie Dorr, Richard Schwartz, Linnea Micciulla, and John Makhoul. 2006. A study of translation edit rate with targeted human annotation. In Proceedings of association for machine translation in the Americas, pages 223-231.
30. Matthew G Snover, Nitin Madnani, Bonnie Dorr, and Richard Schwartz. 2009. Ter-plus: paraphrase, semantic, and alignment enhancements to translation edit rate. Machine Translation, 23(2-3):117-127.
31. Richard Socher, Eric H Huang, Jeffrey Pennin, Christopher D Manning, and Andrew Y Ng. 2011. Dynamic pooling and unfolding recursive autoencoders for paraphrase detection. In Advances in Neural Information Processing Systems, pages 801-809.
32. Joseph Turian, Lev Ratinov, and Yoshua Bengio. 2010. Word representations: a simple and general method for semi-supervised learning. In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, pages 384-394.
33. Pascal Vincent, Hugo Larochelle, Isabelle Lajoie, Yoshua Bengio, and Pierre-Antoine Manzagol. 2010. Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion. The Journal of Machine Learning Research, 11:3371-3408.
34. Stephen Wan, Mark Dras, Robert Dale, and Cécile Paris. 2006. Using dependency-based features to take the "para-farce" out of paraphrase. In Proceedings of the Australasian Language Technology Workshop, volume 2006.
35. Pengcheng Wu, Steven CH Hoi, Hao Xia, Peilin Zhao, Dayong Wang, and Chunyan Miao. 2013. Online multimodal deep similarity learning with application to image retrieval. In Proceedings of the 21st ACM international conference on Multimedia, pages 153-162. ACM.