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http://dx.doi.org/10.9717/kmms.2020.24.1.106

Research on the Hybrid Paragraph Detection System Using Syntactic-Semantic Analysis  

Kang, Won Seog (Dept. of Computer Education, Andong National University)
Publication Information
Journal of Korea Multimedia Society / v.24, no.1, 2021 , pp. 106-116 More about this Journal
Abstract
To increase the quality of the system in the subjective-type question grading and document classification, we need the paragraph detection. But it is not easy because it is accompanied by semantic analysis. Many researches on the paragraph detection solve the detection problem using the word based clustering method. However, the word based method can not use the order and dependency relation between words. This paper suggests the paragraph detection system using syntactic-semantic relation between words with the Korean syntactic-semantic analysis. This system is the hybrid system of word based, concept based, and syntactic-semantic tree based detection. The experiment result of the system shows it has the better result than the word based system. This system will be utilized in Korean subjective question grading and document classification.
Keywords
Paragraph Detection; Syntactic-Semantic Analysis; Clustering; Similarity;
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Times Cited By KSCI : 1  (Citation Analysis)
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