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A Korean Homonym Disambiguation Model Based on Statistics Using Weights  

김준수 (울산대학교 컴퓨터정보통신학과)
최호섭 (울산대학교 컴퓨터정보통신학과)
옥철영 (울산대학교 컴퓨터정보통신공학부)
Publication Information
Journal of KIISE:Software and Applications / v.30, no.11, 2003 , pp. 1112-1123 More about this Journal
Abstract
WSD(word sense disambiguation) is one of the most difficult problems in Korean information processing. The Bayesian model that used semantic information, extracted from definition corpus(1 million POS-tagged eojeol, Korean dictionary definitions), resulted in accuracy of 72.08% (nouns 78.12%, verbs 62.45%). This paper proposes the statistical WSD model using NPH(New Prior Probability of Homonym sense) and distance weights. We select 46 homonyms(30 nouns, 16 verbs) occurred high frequency in definition corpus, and then we experiment the model on 47,977 contexts from ‘21C Sejong Corpus’(3.5 million POS-tagged eojeol). The WSD model using NPH improves on accuracy to average 1.70% and the one using NPH and distance weights improves to 2.01%.
Keywords
Word Sense Disambiguation; WSD; Semantic Information; Homograph;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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