Brundlefly at SemEval-2016 task 12: Recurrent neural networks vs. joint inference for clinical temporal information extraction

SemEval 2016 - 10th International Workshop on Semantic Evaluation, Proceedings

Volumn , Issue , 2016, Pages 1274-1279

  Fries, Jason Alan ^a  

^a STANFORD UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); INFORMATION RETRIEVAL SYSTEMS; SEMANTICS;

CANONICALIZATION; CLINICAL NOTES; DOCUMENT SETS; ENTITY EXTRACTIONS; SMALL SCALE; STRUCTURED PREDICTION; TEMPORAL INFORMATION EXTRACTION; TRAINING DATA;

RECURRENT NEURAL NETWORKS;

EID: 85019682515     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.18653/v1/s16-1198     Document Type: Conference Paper

References (16)

1. Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, James Bergstra, Ian J. Goodfellow, Arnaud Bergeron, Nicolas Bouchard, and Yoshua Bengio. 2012. Theano: new features and speed improvements. Deep Learning and Unsupervised Feature Learning NIPS 2012 Workshop.
2. Steven Bethard, Leon Derczynski, Guergana Savova, Guergana Savova, James Pustejovsky, and Marc Verhagen. 2015. Semeval-2015 task 6: Clinical tempeval. Proc. SemEval.
3. Steven Bethard, Guergana Savova, Wei-Te Chen, Leon Derczynski, James Pustejovsky, and Marc Verhagen. 2016. Semeval-2016 task 12: Clinical tempeval. In Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval 2016), San Diego, California, June. Association for Computational Linguistics.
4. Junyoung Chung, Çaglar Gülçehre, KyungHyun Cho, and Yoshua Bengio. 2014. Empirical evaluation of gated recurrent neural networks on sequence modeling. CoRR, abs/1412.3555.
5. Jeffrey L Elman. 1990. Finding structure in time. Cognitive science, 14(2):179-211.
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. Jason Fries. 2015. Modeling Words for Online Sexual Behavior Surveillance and Clinical Text Information Extraction. Ph. D. thesis, University of Iowa.
8. Sepp Hochreiter and Jürgen Schmidhuber. 1997. Long short-term memory. Neural computation, 9(8):1735-1780.
9. Grégoire Mesnil, Xiaodong He, Li Deng, and Yoshua Bengio. 2013. Investigation of recurrent-neuralnetwork architectures and learning methods for spoken language understanding. In INTERSPEECH, pages 3771-3775.
10. Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013. Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781.
11. Razvan Pascanu, Tomas Mikolov, and Yoshua Bengio. 2012. On the difficulty of training recurrent neural networks. arXiv preprint arXiv:1211.5063.
12. Mohammed Saeed, Mauricio Villarroel, Andrew T Reisner, Gari Clifford, Li-Wei Lehman, George Moody, Thomas Heldt, Tin H Kyaw, Benjamin Moody, and Roger G Mark. 2011. Multiparameter intelligent monitoring in intensive care ii (mimic-ii): a publicaccess intensive care unit database. Critical care medicine, 39(5):952.
13. William F Styler IV, Steven Bethard, Sean Finan, Martha Palmer, Sameer Pradhan, Piet C de Groen, Brad Erickson, Timothy Miller, Chen Lin, Guergana Savova, et al. 2014. Temporal annotation in the clinical domain. Transactions of the Association for Computational Linguistics, 2:143-154.
14. Charles Sutton and Andrew McCallum. 2006. An introduction to conditional random fields for relational learning. Introduction to statistical relational learning, pages 93-128.
15. Kai Sheng Tai, Richard Socher, and Christopher D Manning. 2015. Improved semantic representations from tree-structured long short-term memory networks. arXiv preprint arXiv:1503.00075.
16. Ce Zhang. 2015. DeepDive: A Data Management System for Automatic Knowledge Base Construction. Ph. D. thesis, UW-Madison.