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ORCID14th CoNLL 2010: Uppsala, Sweden - Shared Task
- Richárd Farkas, Veronika Vincze, György Szarvas, György Móra, János Csirik:
Proceedings of the Fourteenth Conference on Computational Natural Language Learning: Shared Task, CoNLL 2010, Uppsala, Sweden, July 15-16, 2010. ACL 2010, ISBN 978-1-932432-84-8 - Richárd Farkas, Veronika Vincze, György Móra, János Csirik, György Szarvas:
The CoNLL-2010 Shared Task: Learning to Detect Hedges and their Scope in Natural Language Text. 1-12 - Buzhou Tang, Xiaolong Wang, Xuan Wang, Bo Yuan, Shixi Fan:
A Cascade Method for Detecting Hedges and their Scope in Natural Language Text. 13-17 - Andreas Vlachos, Mark Craven:
Detecting Speculative Language Using Syntactic Dependencies and Logistic Regression. 18-25 - Maria Georgescul:
A Hedgehop over a Max-Margin Framework Using Hedge Cues. 26-31 - Feng Ji, Xipeng Qiu, Xuanjing Huang:
Detecting Hedge Cues and their Scopes with Average Perceptron. 32-39 - Roser Morante, Vincent Van Asch, Walter Daelemans:
Memory-Based Resolution of In-Sentence Scopes of Hedge Cues. 40-47 - Erik Velldal, Lilja Øvrelid, Stephan Oepen:
Resolving Speculation: MaxEnt Cue Classification and Dependency-Based Scope Rules. 48-55 - Marek Rei, Ted Briscoe:
Combining Manual Rules and Supervised Learning for Hedge Cue and Scope Detection. 56-63 - Eraldo R. Fernandes, Carlos E. M. Crestana, Ruy Luiz Milidiú:
Hedge Detection Using the RelHunter Approach. 64-69 - Halil Kilicoglu, Sabine Bergler:
A High-Precision Approach to Detecting Hedges and their Scopes. 70-77 - Xinxin Li, Jianping Shen, Xiang Gao, Xuan Wang:
Exploiting Rich Features for Detecting Hedges and their Scope. 78-83 - Oscar Täckström, Sumithra Velupillai, Martin Hassel, Gunnar Eriksson, Hercules Dalianis, Jussi Karlgren:
Uncertainty Detection as Approximate Max-Margin Sequence Labelling. 84-91 - Shaodian Zhang, Hai Zhao, Guodong Zhou, Bao-Liang Lu:
Hedge Detection and Scope Finding by Sequence Labeling with Procedural Feature Selection. 92-99 - Qi Zhao, Chengjie Sun, Bingquan Liu, Yong Cheng:
Learning to Detect Hedges and their Scope Using CRF. 100-105 - Huiwei Zhou, Xiaoyan Li, Degen Huang, Zezhong Li, Yuansheng Yang:
Exploiting Multi-Features to Detect Hedges and their Scope in Biomedical Texts. 106-113 - Lin Chen, Barbara Di Eugenio:
A Lucene and Maximum Entropy Model Based Hedge Detection System. 114-119 - David Clausen:
HedgeHunter: A System for Hedge Detection and Uncertainty Classification. 120-125 - Liliana Mamani Sánchez, Baoli Li, Carl Vogel:
Exploiting CCG Structures with Tree Kernels for Speculation Detection. 126-131 - Vinodkumar Prabhakaran:
Uncertainty Learning Using SVMs and CRFs. 132-137 - Nobuyuki Shimizu, Hiroshi Nakagawa:
Features for Detecting Hedge Cues. 138-143 - Ferenc Szidarovszky, Illés Solt, Domonkos Tikk:
A Simple Ensemble Method for Hedge Identification. 144-147 - Erik F. Tjong Kim Sang:
A Baseline Approach for Detecting Sentences Containing Uncertainty. 148-150 - Yi Zheng, Qifeng Dai, Qiming Luo, Enhong Chen:
Hedge Classification with Syntactic Dependency Features Based on an Ensemble Classifier. 151-156
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