The Community for Technology Leaders
Computer Science and Information Engineering, World Congress on (2009)
Los Angeles, California USA
Mar. 31, 2009 to Apr. 2, 2009
ISBN: 978-0-7695-3507-4
pp: 335-338
In this paper, we describe a system for correcting English preposition errors automatically. Non-native English writers often make these errors. Our system uses rules extracted automatically based on preposition context features, such as preceding and following nouns. Additional rules are generated recursively from the extracted rules using Inductive Learning. Our system achieves 82% accuracy and 32% coverage, which are competitive with other systems. Apart from the performance, it has an advantage of being more understandable while investigating why a given preposition was erroneous. This is because we use rules and they give this advantage over maximum entropy approaches.
grammatical error correction, corpus, preposition error

H. Ototake and K. Araki, "Automatic Preposition Errors Correction Using Inductive Learning," 2009 WRI World Congress on Computer Science and Information Engineering, CSIE(CSIE), Los Angeles, CA, 2009, pp. 335-338.
92 ms
(Ver 3.3 (11022016))