Automated postediting of documents
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Maximum entropy models for natural language ambiguity resolution
Maximum entropy models for natural language ambiguity resolution
Head-driven statistical models for natural language parsing
Head-driven statistical models for natural language parsing
Definiteness predictions for Japanese noun phrases
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Memory-based learning for article generation
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
Web-based models for natural language processing
ACM Transactions on Speech and Language Processing (TSLP)
A feedback-augmented method for detecting errors in the writing of learners of English
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
User input and interactions on Microsoft Research ESL Assistant
EdAppsNLP '09 Proceedings of the Fourth Workshop on Innovative Use of NLP for Building Educational Applications
Language modeling for determiner selection
NAACL-Short '07 Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers
English Article Correction System Using Semantic Category Based Inductive Learning Rules
AI '09 Proceedings of the 22nd Australasian Joint Conference on Advances in Artificial Intelligence
ACL-IJCNLP '09 Proceedings of the Third Linguistic Annotation Workshop
Using mostly native data to correct errors in learners' writing: a meta-classifier approach
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Grammatical error correction with alternating structure optimization
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Exploiting learners' tendencies for detecting english determiner errors
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part II
A meta learning approach to grammatical error correction
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Short Papers - Volume 2
Evidence in automatic error correction improves learners' english skill
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume 2
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One common mistake made by non-native speakers of English is to drop the articles a, an, or the. We apply the log-linear model to automatically restore missing articles based on features of the noun phrase. We first show that the model yields competitive results in article generation. Further, we describe methods to adjust the model with respect to the initial quality of the sentence. Our best results are 20.5% article error rate (insertions, deletions and substitutions) for sentences where 30% of the articles have been dropped, and 38.5% for those where 70% of the articles have been dropped.