Conference on Computational Natural Language Learning (2010)
Proceedings of the Fourteenth Conference on Computational Natural Language Learning
Proceedings of the Fourteenth Conference on Computational Natural Language Learning
Mirella Lapata
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Anoop Sarkar
Improvements in Unsupervised Co-Occurrence Based Parsing
Christian Hänig
Viterbi Training Improves Unsupervised Dependency Parsing
Valentin I. Spitkovsky
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Hiyan Alshawi
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Daniel Jurafsky
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Christopher D. Manning
Driving Semantic Parsing from the World’s Response
James Clarke
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Dan Goldwasser
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Ming-Wei Chang
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Dan Roth
Efficient, Correct, Unsupervised Learning for Context-Sensitive Languages
Alexander Clark
Identifying Patterns for Unsupervised Grammar Induction
Jesús Santamaría
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Lourdes Araujo
Learning Better Monolingual Models with Unannotated Bilingual Text
David Burkett
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Slav Petrov
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John Blitzer
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Dan Klein
(Invited Talk) Clueless: Explorations in Unsupervised, Knowledge-Lean Extraction of Lexical-Semantic Information
Lillian Lee
(Invited Talk) Bayesian Hidden Markov Models and Extensions
Zoubin Ghahramani
Improved Unsupervised POS Induction Using Intrinsic Clustering Quality and a Zipfian Constraint
Roi Reichart
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Raanan Fattal
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Ari Rappoport
Syntactic and Semantic Structure for Opinion Expression Detection
Richard Johansson
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Alessandro Moschitti
Type Level Clustering Evaluation: New Measures and a POS Induction Case Study
Roi Reichart
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Omri Abend
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Ari Rappoport
Recession Segmentation: Simpler Online Word Segmentation Using Limited Resources
Constantine Lignos
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Charles Yang
Computing Optimal Alignments for the IBM-3 Translation Model
Thomas Schoenemann
Semi-Supervised Recognition of Sarcasm in Twitter and Amazon
Dmitry Davidov
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Oren Tsur
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Ari Rappoport
Learning Probabilistic Synchronous CFGs for Phrase-Based Translation
Markos Mylonakis
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Khalil Sima’an
A Semi-Supervised Batch-Mode Active Learning Strategy for Improved Statistical Machine Translation
Sankaranarayanan Ananthakrishnan
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Rohit Prasad
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David Stallard
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Prem Natarajan
Improving Word Alignment by Semi-Supervised Ensemble
Shujian Huang
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Kangxi Li
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Xinyu Dai
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Jiajun Chen
A Comparative Study of Bayesian Models for Unsupervised Sentiment Detection
Chenghua Lin
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Yulan He
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Richard Everson
A Hybrid Approach to Emotional Sentence Polarity and Intensity Classification
Jorge Carrillo de Albornoz
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Laura Plaza
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Pablo Gervás
Cross-Caption Coreference Resolution for Automatic Image Understanding
Micah Hodosh
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Peter Young
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Cyrus Rashtchian
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Julia Hockenmaier
Improved Natural Language Learning via Variance-Regularization Support Vector Machines
Shane Bergsma
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Dekang Lin
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Dale Schuurmans
Online Entropy-Based Model of Lexical Category Acquisition
Grzegorz Chrupała
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Afra Alishahi
Tagging and Linking Web Forum Posts
Su Nam Kim
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Li Wang
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Timothy Baldwin
Joint Entity and Relation Extraction Using Card-Pyramid Parsing
Rohit J. Kate
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Raymond Mooney
Distributed Asynchronous Online Learning for Natural Language Processing
Kevin Gimpel
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Dipanjan Das
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Noah A. Smith
On Reverse Feature Engineering of Syntactic Tree Kernels
Daniele Pighin
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Alessandro Moschitti
Inspecting the Structural Biases of Dependency Parsing Algorithms
Yoav Goldberg
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Michael Elhadad
Proceedings of the Fourteenth Conference on Computational Natural Language Learning – Shared Task
Proceedings of the Fourteenth Conference on Computational Natural Language Learning – Shared Task
Richárd Farkas
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Veronika Vincze
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György Szarvas
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György Móra
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János Csirik
The CoNLL-2010 Shared Task: Learning to Detect Hedges and their Scope in Natural Language Text
Richárd Farkas
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Veronika Vincze
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György Móra
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János Csirik
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György Szarvas
A Cascade Method for Detecting Hedges and their Scope in Natural Language Text
Buzhou Tang
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Xiaolong Wang
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Xuan Wang
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Bo Yuan
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Shixi Fan
Detecting Speculative Language Using Syntactic Dependencies and Logistic Regression
Andreas Vlachos
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Mark Craven
A Hedgehop over a Max-Margin Framework Using Hedge Cues
Maria Georgescul
Detecting Hedge Cues and their Scopes with Average Perceptron
Feng Ji
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Xipeng Qiu
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Xuanjing Huang
Memory-Based Resolution of In-Sentence Scopes of Hedge Cues
Roser Morante
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Vincent Van Asch
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Walter Daelemans
Resolving Speculation: MaxEnt Cue Classification and Dependency-Based Scope Rules
Erik Velldal
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Lilja Øvrelid
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Stephan Oepen
Combining Manual Rules and Supervised Learning for Hedge Cue and Scope Detection
Marek Rei
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Ted Briscoe
Hedge Detection Using the RelHunter Approach
Eraldo Fernandes
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Carlos Crestana
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Ruy Milidiú
A High-Precision Approach to Detecting Hedges and their Scopes
Halil Kilicoglu
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Sabine Bergler
Exploiting Rich Features for Detecting Hedges and their Scope
Xinxin Li
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Jianping Shen
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Xiang Gao
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Xuan Wang
Uncertainty Detection as Approximate Max-Margin Sequence Labelling
Oscar Täckström
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Sumithra Velupillai
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Martin Hassel
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Gunnar Eriksson
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Hercules Dalianis
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Jussi Karlgren
Hedge Detection and Scope Finding by Sequence Labeling with Procedural Feature Selection
Shaodian Zhang
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Hai Zhao
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Guodong Zhou
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Bao-Liang Lu
Learning to Detect Hedges and their Scope Using CRF
Qi Zhao
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Chengjie Sun
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Bingquan Liu
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Yong Cheng
Exploiting Multi-Features to Detect Hedges and their Scope in Biomedical Texts
Huiwei Zhou
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Xiaoyan Li
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Degen Huang
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Zezhong Li
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Yuansheng Yang
A Lucene and Maximum Entropy Model Based Hedge Detection System
Lin Chen
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Barbara Di Eugenio
HedgeHunter: A System for Hedge Detection and Uncertainty Classification
David Clausen
Exploiting CCG Structures with Tree Kernels for Speculation Detection
Liliana Mamani Sánchez
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Baoli Li
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Carl Vogel
Uncertainty Learning Using SVMs and CRFs
Vinodkumar Prabhakaran
Features for Detecting Hedge Cues
Nobuyuki Shimizu
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Hiroshi Nakagawa
A Simple Ensemble Method for Hedge Identification
Ferenc Szidarovszky
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Illés Solt
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Domonkos Tikk
A Baseline Approach for Detecting Sentences Containing Uncertainty
Erik Tjong Kim Sang
Hedge Classification with Syntactic Dependency Features Based on an Ensemble Classifier
Yi Zheng
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Qifeng Dai
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Qiming Luo
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Enhong Chen