Event detection and domain adaptation with 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 2, Issue , 2015, Pages 365-371

  Nguyen, Thien Huu ^a   Grishman, Ralph ^a  

^a POLYTECHNIC UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BACKPROPAGATION; COMPUTATIONAL LINGUISTICS; CONVOLUTION; NEURAL NETWORKS; LINGUISTICS;

CONVOLUTIONAL NEURAL NETWORK; DOMAIN ADAPTATION; EVENT DETECTION; EXTERNAL RESOURCES; FEATURE ENGINEERINGS; FEATURE-BASED; RICH FEATURES; ERROR PROPAGATION; FEATURE BASED APPROACHES; FUNDAMENTAL LIMITATIONS;

NATURAL LANGUAGE PROCESSING SYSTEMS;

EID: 84944030435     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3115/v1/p15-2060     Document Type: Conference Paper

References (32)

1. John Blitzer, Ryan McDonald, and Fernando Pereira. 2006. Domain Adaptation with Structural Corre-spondence Learning. In Proceedings of EMNLP
2. Ronan Collobert and Jason Weston. 2008. A Uni-fied Architecture for Natural Language Processing: Deep Neural Networks with Multitask Learning. In Proceedings of ICML
3. Ronan Collobert, Jason Weston, Leon Bottou, Michael Karlen, Koray Kavukcuoglu and Pavel Kuksa. 2011. Natural Language Processing (Almost) from Scratch. Journal of Machine Learning Research 12:24932537
4. Hal Daume III. 2007. Frustratingly Easy Domain Adaptation. In Proceedings of ACL
5. Prashant Gupta and Heng Ji. 2009. Predicting Un-known Time Arguments Based on Cross-Event Prop-agation. In Proceedings of ACL-UCNLP
6. Geoffrey E. Hinton, Nitish Srivastava, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov. 2012. Improving Neural Networks by Preventing Co-Adaptation of Feature Detectors. CoRR, abs/1207.0580
7. Yu Hong, Jianfeng Zhang, Bin Ma, Jian-Min Yao, Guodong Zhou, and Qiaoming Zhu. 2011. Using Cross-entity Inference to Improve Event Extraction. In Proceedings of ACL
8. Baotian Hu, Zhengdong Lu, Hang Li, Qingcai Chen. 2014. Convolutional Neural Network Architectures for Matching Natural Language Sentences. In Pro-ceedings of NIPS
9. Ruihong Huang and Ellen Riloff. 2012. Modeling Tex-tual Cohesion for Event Extraction. In Proceedings of AAAI
10. Heng Ji and Ralph Grishman. 2008. Refining Event Extraction through Cross-Document Inference. In Proceedings of ACL
11. Nal Kalchbrenner, Edward Grefenstette and Phil Blun-som. 2014. A Convolutional Neural Network for Modeling Sentences. In Proceedings of ACL
12. Yoon Kim. 2014. Convolutional Neural Networks for Sentence Classification. In Proceedings of EMNLP
13. Yann LeCun, Leon Bottou, Yoshua Bengio and Patrick Haffner. 1988. Gradient-based Learning Applied to Document Recognition. In Proceedings of the IEEE, 86(11):22782324
14. Peifeng Li, Qiaoming Zhu, and Guodong Zhou. 2013a. Argument Inference from Relevant Event Mentions in Chinese Argument Extraction. In Proceedings of ACL
15. Qi Li, Heng Ji, and Liang Huang. 2013b. Joint Event Extraction via Structured Prediction with Global Features. In Proceedings of ACL
16. Shasha Liao and Ralph Grishman. 2010. Using Doc-ument Level Cross-event Inference to Improve Event Extraction. In Proceedings of ACL
17. Shasha Liao and Ralph Grishman. 2011. Acquiring Topic Features to Improve Event Extraction: in Pre-selected and Balanced Collections. In Proceedings RANLP
18. David McClosky, Eugene Charniak, and Mark John-son. 2010. Automatic Domain Adaptation for Pars-ing. In Proceedings of HLT-NAACL
19. David McClosky, Mihai Surdeanu, and Chris Manning. 2011. Event Extraction as Dependency Parsing. In Proceedings of ACL-HLT
20. Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013. Distributed Repre-sentations of Words and Phrases and their Compo-sitionality. In Proceedings of NIPS
21. Thien Huu Nguyen and Ralph Grishman. 2014. Em-ploying Word Representations and Regularization for Domain Adaptation of Relation Extraction. In Proceedings of ACL
22. Thien Huu Nguyen and Ralph Grishman. 2015. Re-lation Extraction: Perspective from Convolutional Neural Networks. In Proceedings of the NAACL Workshop on Vector Space Modeling for NLP (VSM)
23. Siddharth Patwardhan and Ellen Rilof. 2009. A Uni-fied Model of Phrasal and Sentential Evidence for Information Extraction. In Proceedings of EMNLP
24. Barbara Plank and Alessandro Moschitti. 2013. Em-bedding Semantic Similarity in Tree Kernels for Do-main Adaptation of Relation Extraction. In Proceed-ings of ACL
25. Sebastian Riedel and Andrew McCallum. 2011. Fast and Robust Joint Models for Biomedical Event Ex-traction. In Proceedings of EMNLP
26. Sebastian Riedel and Andrew McCallum. 2011. Ro-bust Biomedical Event Extraction with Dual Decom-position and Minimal Domain Adaptation. In Pro-ceedings of the BioNLP Shared Task 2011 Work-shop
27. Yelong Shen, Xiaodong He, Jianfeng Gao, Li Deng and Gregoire Mesnil. 2014. Learning Semantic Repre-sentations Using Convolutional Neural Networks for Web Search. In Proceedings of WWW
28. Joseph Turian, Lev Ratinov, and Yoshua Bengio. 2010. Word Representations: A Simple and General Method for Semi-supervised Learning. In Proceed-ings of ACL
29. Deepak Venugopal, Chen Chen, Vibhav Gogate and Vincent Ng. 2014. Relieving the Computational Bottleneck: Joint Inference for Event Extraction with High-Dimensional Features. In Proceedings of EMNLP
30. Wen-Taii Yih, Xiaodong He, and Christopher Meek. 2014. Semantic Parsing for Single-Relation Ques-tion Answering. In Proceedings of ACL
31. Matthew D. Zeiler. 2012. ADADELTA: An Adaptive Learning Rate Method. CoRR, abs/1212.5701
32. Daojian Zeng, Kang Liu, Siwei Lai, Guangyou Zhou and Jun Zhao. 2014. Relation Classification via Convolutional Deep Neural Network. In Proceed-ings ofCOLING