Assignment Semantic Category of a Word using Word Embedding and Synonyms 


Vol. 44,  No. 9, pp. 946-953, Sep.  2017
10.5626/JOK.2017.44.9.946


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  Abstract

Semantic Role Decision defines the semantic relationship between the predicate and the arguments in natural language processing (NLP) tasks. The semantic role information and semantic category information should be used to make Semantic Role Decisions. The Sejong Electronic Dictionary contains frame information that is used to determine the semantic roles. In this paper, we propose a method to extend the Sejong electronic dictionary using word embedding and synonyms. The same experiment is performed using existing word-embedding and retrofitting vectors. The system performance of the semantic category assignment is 32.19%, and the system performance of the extended semantic category assignment is 51.14% for words that do not appear in the Sejong electronic dictionary of the word using the word embedding. The system performance of the semantic category assignment is 33.33%, and the system performance of the extended semantic category assignment is 53.88% for words that do not appear in the Sejong electronic dictionary of the vector using retrofitting. We also prove it is helpful to extend the semantic category word of the Sejong electronic dictionary by assigning the semantic categories to new words that do not have assigned semantic categories.


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  Cite this article

[IEEE Style]

D. Park and J. Cha, "Assignment Semantic Category of a Word using Word Embedding and Synonyms," Journal of KIISE, JOK, vol. 44, no. 9, pp. 946-953, 2017. DOI: 10.5626/JOK.2017.44.9.946.


[ACM Style]

Da-Sol Park and Jeong-Won Cha. 2017. Assignment Semantic Category of a Word using Word Embedding and Synonyms. Journal of KIISE, JOK, 44, 9, (2017), 946-953. DOI: 10.5626/JOK.2017.44.9.946.


[KCI Style]

박다솔, 차정원, "워드 임베딩과 유의어를 활용한 단어 의미 범주 할당," 한국정보과학회 논문지, 제44권, 제9호, 946~953쪽, 2017. DOI: 10.5626/JOK.2017.44.9.946.


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