Search right and thou shalt find... Using Web Queries for Learner Error Detection

by Michael Gamon , Claudia Leacock
Citations:3 - 0 self

Active Bibliography

Signed – Joachim Wagner, Magister Artium, Prof Josef Van Genabith
Large-Scale Semi-Supervised Learning for Natural Language Processing – Shane Bergsma - 2010
3 Using Mostly Native Data to Correct Errors in Learners’ Writing: a MetaClassifier Approach. Human Language Technologies: The 2010 – Michael Gamon - 2010
40 The web as a baseline: Evaluating the performance of unsupervised web-based models for a range of nlp tasks – Mirella Lapata, Frank Keller - 2004
Using Statistical Techniques and Web Search to Correct ESL Errors – unknown authors
16 Using an error-annotated learner corpus to develop and ESL/EFL error correction system – Na-rae Han, Joel Tetreault, Soo-hwa Lee, Jin-young Ha - 2010
2 Using error-annotated ESL data to develop an ESL error correction system – Na-rae Han, Joel Tetreault, Soo-hwa Lee, Jin-young Ha - 2010
31 Using the Web to Overcome Data Sparseness – Frank Keller, Maria Lapata, Olga Ourioupina - 2002
137 Using the web to obtain frequencies for unseen bigrams. Comput. Linguist – Frank Keller, Mirella Lapata - 2003
Syntax-Driven Machine Translation as a Model of ESL Revision – unknown authors
3 “Is the Sky Pure Today?” AwkChecker: An Assistive Tool for Detecting and Correcting Collocation Errors – Taehyun Park, Edward Lank, Pascal Poupart, Michael Terry
2 High-Order Sequence Modeling for Language Learner Error Detection – Michael Gamon
Correcting Different Types of Errors in Texts – Aminul Islam, Diana Inkpen
UdS at the CoNLL 2013 Shared Task – Desmond Darma Putra, Lili Szabó
CALICO Journal, 26(3) – Diane M. Napolitano, A Stent
Effective Use of Chinese Structural Auxiliaries for Chinese Parsing * – Yun Jin A, Qing Li B, Yingshun Wu A, Young-gil Kim A
4 Semantic Classification of Noun Phrases Using Web Counts and Learning Algorithms – Paul Nulty
5 Exploring the Data-Driven Prediction of Prepositions in English – Anas Elghafari, Detmar Meurers, Holger Wunsch, Universität Tübingen
A Noisy Channel Model Framework for Grammatical Correction – L. Amber Wilcox-o’hearn