Abstract
In this paper, we describe a system for automatic correction of English. Our system uses rules based on article context features, and generates new abstract rules by Semantic Category Based Inductive Learning that we proposed before. In the experiments, we achieve 93% precision with the best set of parameters. This method scored higher than our previous system, and is competitive with a related method for the same task.
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Ototake, H., Araki, K. (2009). English Article Correction System Using Semantic Category Based Inductive Learning Rules. In: Nicholson, A., Li, X. (eds) AI 2009: Advances in Artificial Intelligence. AI 2009. Lecture Notes in Computer Science(), vol 5866. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10439-8_60
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DOI: https://doi.org/10.1007/978-3-642-10439-8_60
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10438-1
Online ISBN: 978-3-642-10439-8
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