Fujishima, Satoru and Ishizaki, Shun (2011) Automated Detection of Usage Errors in non-native English Writing. In: IES 2011-Emerging Technology for Better Human Life.
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Abstract
In an investigation of the use of a novelty detection algorithm for identifying inappropriate word combinations in a raw English corpus, we employ an unsupervised detection algorithm based on the one- class support vector machines (OC-SVMs) and extract sentences containing word sequences whose frequency of appearance is significantly low in native English writing. Combined with n-gram language models and document categorization techniques, the OC-SVM classifier assigns given sentences into two different groups; the sentences containing errors and those without errors. Accuracies are 79.30 % with bigram model, 86.63 % with trigram model, and 34.34 % with four-gram model.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science |
| Depositing User: | Satria Hardinata |
| Date Deposited: | 14 Nov 2011 12:15 |
| Last Modified: | 14 Nov 2011 12:15 |
| URI: | http://repo.pens.ac.id/id/eprint/1470 |
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