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Title: KU Leuven at HOO-2012: A hybrid approach to detection and correction of determiner and preposition errors in non-native English text
Authors: Quan, Li ×
Kolomiyets, Oleksandr
Moens, Marie-Francine #
Issue Date: 2012
Publisher: ACL
Host Document: Proceedings of the NAACL-HLT 2012 workshop on innovative use of NLP for building educational applications pages:263-271
Conference: NAACL-HLT 2012 workshop on innovative use of NLP for building educational applications location:Montreal, Canada date:7 June 2012
Abstract: In this paper we describe the technical implementation of our system that participated in the Helping Our Own 2012 Shared Task (HOO-2012). The system employs a number of preprocessing steps and machine learning
classifiers for correction of determiner and preposition errors in non-native English texts. We use maximum entropy classifiers trained on the provided HOO-2012 development data and a large high-quality English text collection.
The system proposes a number of highly probable corrections, which are evaluated by a language model and compared with the original
text. A number of deterministic rules are used to increase the precision and recall of the system. Our system is ranked among the three best performing HOO-2012 systems with a precision of 31.15%, recall of 22.08% and F1-score of 25.84% for correction of determiner
and preposition errors combined.
Publication status: published
KU Leuven publication type: IC
Appears in Collections:Informatics Section
× corresponding author
# (joint) last author

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