• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.353-358
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• 2021

This study provides the syntactic analysis for the agreement attraction by proposing three types of syntactic subject-verb agreement. Because subject-verb number agreement codifies the link between a predicate and its subject, it must be the purely syntactic processes of the head-to-head agreement or the feature percolation, where relevant agreement features percolate upward or downward through the hierarchical syntactic structure. The agreement errors are not affected by linear proximity or minimal interference, but instead are affected by the hierarchical relationship between an agreement target and a local attractor. The data in this paper includes the complex noun phrases with a modifier PP or a relative clause CP. Here, the [+PL] feature is suggested to be a local attractor for subject-verb agreement errors as a strong feature. Therefore, speakers tend to erroneously produce plural agreement for a singular subject in a main clause due to a plural NP in a modifier PP or plural agreement for a singular subject in a relative clause due to plural main subject.

• Journal of Digital Convergence
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• v.18 no.2
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• pp.285-290
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• 2020

This study focus on improving the text language proficiency regarding users' written text. In order to tone up accuracy improvement in writing, Computer Assisted Language Learning(CALL) can be primarily used as one of the most efficient tools. This study proposes a English Grammar Checking Application that can improve the accuracy over the current applications. The proposed system is capable of defining the difference between a Noun and a Noun Phrase which is critical in improving grammar accuracy for those who use Englilsh as a foreign language in English writing.