| ACL 2010 CD | Conference ON CD | ACL 2010 ONLINE | ACL ONLINE |
Conference PROGRAM
Thursday, July 15, 2010 | |
| 9:00–9:15 | Opening Remarks |
| Session 1: Parsing (9:15–10:30) | |
| 9:15–9:40 | Improvements in Unsupervised Co-Occurrence Based Parsing Christian Hänig |
| 9:40–10:05 | Viterbi Training Improves Unsupervised Dependency Parsing Valentin I. Spitkovsky, Hiyan Alshawi, Daniel Jurafsky and Christopher D. Manning |
| 10:05–10:30 | Driving Semantic Parsing from the World’s Response James Clarke, Dan Goldwasser, Ming-Wei Chang and Dan Roth |
| 10:30–11:00 | Break |
| Session 2: Grammar Induction (11:00–12:15) | |
| 11:00–11:25 | Efficient, Correct, Unsupervised Learning for Context-Sensitive Languages Alexander Clark |
| 11:25–11:50 | Identifying Patterns for Unsupervised Grammar Induction Jesús Santamaría and Lourdes Araujo |
| 11:50–12:15 | Learning Better Monolingual Models with Unannotated Bilingual Text David Burkett, Slav Petrov, John Blitzer and Dan Klein |
| 12:15–14:15 | Lunch |
| 14:15–15:30 | (Invited Talk) Clueless: Explorations in Unsupervised, Knowledge-Lean Extraction of Lexical-Semantic Information Lillian Lee |
| 15:30–16:00 | Break |
| CoNLL 2010 Shared Task, Overview and Oral Presentations (16:00–17:30) | |
| 16:00–16:20 | 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 |
| 16:20–16:30 | A Cascade Method for Detecting Hedges and their Scope in Natural Language Text Buzhou Tang, Xiaolong Wang, Xuan Wang, Bo Yuan and Shixi Fan |
| 16:30–16:40 | Detecting Speculative Language using Syntactic Dependencies and Logistic Regression Andreas Vlachos and Mark Craven |
| 16:40–16:50 | A Hedgehop over a Max-margin Framework using Hedge Cues Maria Georgescul |
| 16:50–17:00 | Detecting Hedge Cues and their Scopes with Average Perceptron Feng Ji, Xipeng Qiu and Xuanjing Huang |
| 17:00–17:10 | Memory-based Resolution of In-sentence Scopes of Hedge Cues Roser Morante, Vincent Van Asch and Walter Daelemans |
| 17:10–17:20 | Resolving Speculation: MaxEnt Cue Classification and Dependency-Based Scope Rules Erik Velldal, Lilja vrelid and Stephan Oepen |
| 17:20–17:30 | Combining Manual Rules and Supervised Learning for Hedge Cue and Scope Detection Marek Rei and Ted Briscoe |
| Shared Task Discussion Panel (17:30–18:00) | |
Friday, July 16, 2010 | |
| 9:15–10:30 | (Invited Talk) Bayesian Hidden Markov Models and Extensions Zoubin Ghahramani |
| 10:30–11:00 | Break |
| Joint Poster Session: Main conference and shared task posters (11:00–12:30) | |
| 11:00–12:30 | Main conference posters |
| Improved Unsupervised POS Induction Using Intrinsic Clustering Quality and a Zipfian Constraint Roi Reichart, Raanan Fattal and Ari Rappoport | |
| Syntactic and Semantic Structure for Opinion Expression Detection Richard Johansson and Alessandro Moschitti | |
| Type Level Clustering Evaluation: New Measures and a POS Induction Case Study Roi Reichart, Omri Abend and Ari Rappoport | |
| Recession Segmentation: Simpler Online Word Segmentation Using Limited Resources Constantine Lignos and Charles Yang | |
| Computing Optimal Alignments for the IBM-3 Translation Model Thomas Schoenemann | |
| Semi-Supervised Recognition of Sarcasm in Twitter and Amazon Dmitry Davidov, Oren Tsur and Ari Rappoport | |
| Learning Probabilistic Synchronous CFGs for Phrase-Based Translation Markos Mylonakis and Khalil Sima’an | |
| A Semi-Supervised Batch-Mode Active Learning Strategy for Improved Statistical Machine Translation Sankaranarayanan Ananthakrishnan, Rohit Prasad, David Stallard and Prem Natarajan | |
| Improving Word Alignment by Semi-Supervised Ensemble Shujian Huang, Kangxi Li, Xinyu Dai and Jiajun Chen | |
| A Comparative Study of Bayesian Models for Unsupervised Sentiment Detection Chenghua Lin, Yulan He and Richard Everson | |
| A Hybrid Approach to Emotional Sentence Polarity and Intensity Classification Jorge Carrillo de Albornoz, Laura Plaza and Pablo Gervás | |
| Cross-Caption Coreference Resolution for Automatic Image Understanding Micah Hodosh, Peter Young, Cyrus Rashtchian and Julia Hockenmaier | |
| Improved Natural Language Learning via Variance-Regularization Support Vector Machines Shane Bergsma, Dekang Lin and Dale Schuurmans | |
| 11:00–12:30 | Shared Task p
osters: Systems for Shared Task 1 and 2 Hedge Detection using the R elHunter Approach Eraldo Fernandes, Carlos Crestana and Ruy Milidiú A High-Precision Approach to Detecting Hedges and Their Scopes Halil Kilicoglu and Sabine Bergler Exploiting Rich Features for Detecting Hedges and Their Scope Xinxin Li, Jianping Shen, Xiang Gao and Xuan Wang Uncertainty Detection as Approximate Max-Margin Sequence Labelling Oscar Täckström, Sumithra Velupillai, Martin Hassel, Gunnar Eriksson, Hercules Dalianis and Jussi Karlgren Hedge Detection and Scope Finding by Sequence Labeling with Procedural Feature Selection Shaodian Zhang, Hai Zhao, Guodong Zhou and Bao-liang Lu Learning to Detect Hedges and their Scope using CRF Qi Zhao, Chengjie Sun, Bingquan Liu and Yong Cheng Exploiting Multi-Features to Detect Hedges and Their Scope in Biomedical Texts Huiwei Zhou, Xiaoyan Li, Degen Huang, Zezhong Li and Yuansheng Yang |
| 11:00–12:30 | Shared Task p
osters: Systems for Shared Task 1 A Lucene and Maximum Entropy Model Based Hedge Detection System Lin Chen and Barbara Di Eugenio HedgeHunter: A System for Hedge Detection and Uncertainty Classification David Clausen Uncertainty Learning using SVMs and CRFs Vinodkumar Prabhakaran Exploiting CCG Structures with Tree Kernels for Speculation Detection Liliana Paola Mamani Sanchez, Baoli Li and Carl Vogel Features for Detecting Hedge Cues Nobuyuki Shimizu and Hiroshi Nakagawa A Simple Ensemble Method for Hedge Identification Ferenc Szidarovszky, Illés Solt and 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, Qifeng Dai, Qiming Luo and Enhong Chen |
| 12:30–14:00 | Lunch |
| Session 3: Semantics and Information Extraction (14:00–15:15) | |
| 14:00–14:25 | Online Entropy-Based Model of Lexical Category Acquisition Grzegorz Chrupała and Afra Alishahi |
| 14:25–14:50 | Tagging and Linking Web Forum Posts Su Nam Kim, Li Wang and Timothy Baldwin |
| 14:50–15:15 | Joint Entity and Relation Extraction Using Card-Pyramid Parsing Rohit J. Kate and Raymond Mooney |
| 15:30–16:00 | Break |
| Session 4: Machine learning (16:00–17:15) | |
| 16:00–16:25 | Distributed Asynchronous Online Learning for Natural Language Processing Kevin Gimpel, Dipanjan Das and Noah A. Smith |
| 16:25–16:50 | On Reverse Feature Engineering of Syntactic Tree Kernels Daniele Pighin and Alessandro Moschitti |
| 16:50–17:15 | Inspecting the Structural Biases of Dependency Parsing Algorithms Yoav Goldberg and Michael Elhadad |
| Closing Session (17:15–17:45) | |
| 17:15–17:45 | SIGNLL Business Meeting and Best Paper Award |