Event extraction via dynamic multi-pooling convolutional neural networks

ACL-IJCNLP 2015 - 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, Proceedings of the Conference

Volumn 1, Issue , 2015, Pages 167-176

  Chen, Yubo ^a   Xu, Liheng ^a   Liu, Kang ^a   Zeng, Daojian ^a   Zhao, Jun ^a  

^a INSTITUTE OF AUTOMATION   (China)

Author keywords

[No Author keywords available]

Indexed keywords

BACKPROPAGATION; COMPUTATIONAL LINGUISTICS; CONVOLUTION; EXTRACTION; INFORMATION ANALYSIS; MULTILAYER NEURAL NETWORKS; SEMANTICS;

CONVOLUTIONAL NEURAL NETWORK; DATA SPARSITY PROBLEMS; ERROR PROPAGATION; EVENT EXTRACTION; NATURAL LANGUAGE PROCESSING; STATE-OF-THE-ART METHODS; TRADITIONAL APPROACHES; WORD REPRESENTATIONS;

NATURAL LANGUAGE PROCESSING SYSTEMS;

EID: 84943802037     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3115/v1/p15-1017     Document Type: Conference Paper

References (25)

1. David Ahn. 2006. The stages of event extraction. In Proceedings of ACL, pages 1-8.
2. Marco Baroni, Georgiana Dinu, and Germán Kruszewski. 2014. Dont count, predict! a systematic comparison of context-counting vs. context-predicting semantic vectors. In Proceedings of ACL, pages 238-247.
3. Yoshua Bengio, Réjean Ducharme, Pascal Vincent, and Christian Jauvin. 2003. A neural probabilistic language model. The Journal of Machine Learning Research, 3:1137-1155.
4. Chen Chen and V Incent NG. 2012. Joint modeling for chinese event extraction with rich linguistic features. In Proceedings of COLING, pages 529-544.
5. Ronan Collobert, Jason Weston, Ĺeon Bottou, Michael Karlen, Koray Kavukcuoglu, and Pavel Kuksa. 2011. Natural language processing (almost) from scratch. The Journal of Machine Learning Research, 12:2493-2537.
6. Dumitru Erhan, Yoshua Bengio, Aaron Courville, Pierre-Antoine Manzagol, Pascal Vincent, and Samy Bengio. 2010. Why does unsupervised pre-Training help deep learning? The Journal of Machine Learning Research, 11:625-660.
7. Prashant Gupta and Heng Ji. 2009. Predicting unknown time arguments based on cross-event propagation. In Proceedings of ACL-IJCNLP, pages 369-372.
8. Geoffrey E Hinton, Nitish Srivastava, Alex Krizhevsky, Ilya Sutskever, and Ruslan R Salakhutdinov. 2012. Improving neural networks by preventing coadaptation of feature detectors. arXiv preprint arXiv:1207.0580.
9. Yu Hong, Jianfeng Zhang, Bin Ma, Jianmin Yao, Guodong Zhou, and Qiaoming Zhu. 2011. Using cross-entity inference to improve event extraction. In Proceedings of ACL-HLT, pages 1127-1136.
10. Heng Ji and Ralph Grishman. 2008. Refining event extraction through cross-document inference. In Proceedings of ACL, pages 254-262.
11. Nal Kalchbrenner and Phil Blunsom. 2013. Recurrent convolutional neural networks for discourse compositionality. arXiv preprint arXiv:1306.3584.
12. Nal Kalchbrenner, Edward Grefenstette, and Phil Blunsom. 2014. A convolutional neural network for modelling sentences. arXiv preprint arXiv:1404.2188.
13. Yoon Kim. 2014. Convolutional neural networks for sentence classification. arXiv preprint arXiv:1408.5882.
14. Siwei Lai, Liheng Xu, Kang Liu, and Jun Zhao. 2015. Recurrent convolutional neural networks for text classification. In Proceedings of AAAI.
15. Qi Li, Heng Ji, and Liang Huang. 2013. Joint event extraction via structured prediction with global features. In Proceedings of ACL, pages 73-82.
16. Qi Li, Heng Ji, Yu Hong, and Sujian Li. 2014. Constructing information networks using one single model. In Proceedings of EMNLP, pages 1846-1851.
17. Shasha Liao and Ralph Grishman. 2010. Using document level cross-event inference to improve event extraction. In Proceedings of ACL, pages 789-797.
18. David McClosky, Mihai Surdeanu, and Christopher D Manning. 2011. Event extraction as dependency parsing. In Proceedings of ACL-HLT, pages 1626-1635.
19. Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013a. Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781.
20. Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013b. Distributed representations of words and phrases and their compositionality. In Proceedings of NIPS, pages 3111-3119.
21. Frederic Morin and Yoshua Bengio. 2005. Hierarchical probabilistic neural network language model. In Proceedings of AISTATS, pages 246-252.
22. Joseph Turian, Lev Ratinov, and Yoshua Bengio. 2010. Word representations: A simple and general method for semi-supervised learning. In Proceedings of ACL, pages 384-394.
23. David Yarowsky. 1995. Unsupervised word sense disambiguation rivaling supervised methods. In Proceedings of ACL, pages 189-196.
24. Matthew D Zeiler. 2012. Adadelta: An adaptive learning rate method. arXiv preprint arXiv:1212.5701.
25. Daojian Zeng, Kang Liu, Siwei Lai, Guangyou Zhou, and Jun Zhao. 2014. Relation classification via convolutional deep neural network. In Proceedings of COLING, pages 2335-2344