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. © 2011 Springer-Verlag.
CITATION STYLE
Gotti, F., Langlais, P., Lapalme, G., Charest, S., & Brunelle, É. (2011). Reducing overdetections in a French symbolic grammar checker by classification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6609 LNCS, pp. 390–401). https://doi.org/10.1007/978-3-642-19437-5_32
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