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Proceedings of the Fourteenth Conference on Computational Natural Language Learning

Chairs
Richárd Farkas (University of Szeged)
Veronika Vincze (University of Szeged)
György Szarvas (Universität Darmstadt)
György Móra (University of Szeged)
János Csirik (Hungarian Academy of Sciences)

Full proceedings volume (PDF)
Schedule and author index (HTML)
Bibliography (BibTeX)


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

Last modified on June 19, 2010, 0:55 a.m.