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Improvement of Korean Homograph Disambiguation using Korean Lexical Semantic Network (UWordMap)
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  • Journal title : Journal of KIISE
  • Volume 43, Issue 1,  2016, pp.71-79
  • Publisher : Korean Institute of Information Scientists and Engineers
  • DOI : 10.5626/JOK.2016.43.1.71
 Title & Authors
Improvement of Korean Homograph Disambiguation using Korean Lexical Semantic Network (UWordMap)
Shin, Joon-Choul; Ock, Cheol-Young;
 
 Abstract
Disambiguation of homographs is an important job in Korean semantic processing and has been researched for long time. Recently, machine learning approaches have demonstrated good results in accuracy and speed. Other knowledge-based approaches are being researched for untrained words. This paper proposes a hybrid method based on the machine learning approach that uses a lexical semantic network. The use of a hybrid approach creates an additional corpus from subcategorization information and trains this additional corpus. A homograph tagging phase uses the hypernym of the homograph and an additional corpus. Experimentation with the Sejong Corpus and UWordMap demonstrates the hybrid method is to be effective with an increase in accuracy from 96.51% to 96.52%.
 Keywords
morpheme analyzer;corpus;lexical semantic network;UWordMap;sejong corpus;word sense disambiguation;homograph;
 Language
Korean
 Cited by
1.
한국어 의미분석을 위한 의미자원과 어휘의미분별,신준철;옥철영;

정보과학회지, 2016. vol.34. 8, pp.8-16
1.
Comparing discrimination powers of text and citation-based context types, Scientometrics, 2017, 1588-2861  crossref(new windwow)
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