• KIPS Transactions on Software and Data Engineering
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• v.4 no.1
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• pp.45-56
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• 2015

In this paper, we present a method that can detect context-sensitive word errors and generate correction candidates. Spelling error detection is one of the most widespread research topics, however, the approach proposed in this paper is adjusted for an automated English scoring system. A common strategy in context-sensitive word error detection is using a pre-defined confusion set to generate correction candidates. We automatically generate a confusion set in order to consider the characteristics of sentences written by second-language learners. We define a word error that cannot be detected by a conventional grammar checker because of part-of-speech ambiguity, and propose how to detect the error and generate correction candidates for this kind of error. An experiment is performed on the English writings composed by junior-high school students whose mother tongue is Korean. The f1 value of the proposed method is 70.48%, which shows that our method is promising comparing to the current-state-of-the art.

• Journal of the Korea Society of Computer and Information
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• v.18 no.10
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• pp.173-182
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• 2013

Typographical mistakes made in the writing process of drafts of electronic documents are more common than any other type of errors. The majority of these errors caused by mistyping are regarded as consequently still typo-errors, but a considerable number of them are developed into the grammatical errors and the semantic errors. Pseudo semantic errors among these errors due to typographical errors have more noticeable peculiarities than pure semantic errors between senses of surrounding context words within a sentence. These semantic errors can be detected and corrected by simple algorithm based on the co-occurrence frequency because of their prominent contextual discrepancy. I propose a method for detection and correction based on the co-occurrence frequency in order to detect semantic errors due to typo-errors. The co-occurrence frequency in proposed method is counted for only words with immediate dependency relation, and the cosine similarity measure is used in order to detect pseudo semantic errors. From the presented experimental results, the proposed method is expected to help improve the detecting rate of overall proofreading system by about 2~3%.

• Journal of the Korea Convergence Society
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• v.9 no.11
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• pp.315-324
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• 2018

For Korean learners, writing is a harder part than any other areas in Korean languages. But in the future, the ability to organize and write systematically is essential for future koran languages learners to take classes, do assignments and presentations at school, and then adapt to job situations. Therefore, there is a need to devise a direction for this. In general, writing characteristics are viewed in many ways, including writing productivity, writing complexity, and writing errors. Accordingly, the study provided drawings and A4 paper for Vietnamese Korean learners, Chinese Korean learners, and Korean university students, before writing freely. Based on the their writing results, we looked at syntax factors (total C-units, total number of words), syntax complexity (number of words per C-unit and clause density), and writing errors (postposition, spell errors, and connective suffix, space errors) According to the study, Vietnamese and Chinese Korean language learners showed significantly lower syntax productivity and complexity than Korean university students, and showed more writing errors than Korean students in postposition and clause density. Based on the results of the study, we discussed writing guidelines for Korean languages learners. However, this study did not validate the differences in writing characteristics according to the Korean language level and length of residences for the study subjects. Therefore, it is necessary to consider this in future research.