A technique for computer detection and correction of spelling errors
Communications of the ACM
EasyEnglish: a tool for improving document quality
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
Unsupervised word sense disambiguation rivaling supervised methods
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
GramCheck: a grammar and style checker
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Design and evaluation of grammar checkers in multiple languages
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Parsing Ill-Formed Text Using an Error Grammar
Artificial Intelligence Review
A bag of useful techniques for efficient and robust parsing
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
An improved error model for noisy channel spelling correction
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Treebanks gone bad: Parser evaluation and retraining using a treebank of ungrammatical sentences
International Journal on Document Analysis and Recognition
Adapting a lexicalized-grammar parser to contrasting domains
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Using self-trained bilexical preferences to improve disambiguation accuracy
IWPT '07 Proceedings of the 10th International Conference on Parsing Technologies
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
A generalized method for iterative error mining in parsing results
GEAF '09 Proceedings of the 2009 Workshop on Grammar Engineering Across Frameworks
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We describe the development of an "overdetection" identifier, a system for filtering detections erroneously flagged by a grammar checker. Various families of classifiers have been trained in a supervised way for 14 types of detections made by a commercial French grammar checker. Eight of these were integrated in the most recent commercial version of the system. This is a striking illustration of how a machine learning component can be successfully embedded in Antidote, a robust, commercial, as well as popular natural language application.