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http://dx.doi.org/10.3745/KIPSTB.2003.10B.1.047

Segmenting and Classifying Korean Words based on Syllables Using Instance-Based Learning  

Kim, Jae-Hoon (한국해양대학교 컴퓨터공학과)
Lee, Kong-Joo (이화여자대학교 컴퓨터공학과)
Publication Information
The KIPS Transactions:PartB / v.10B, no.1, 2003 , pp. 47-56 More about this Journal
Abstract
Korean delimits words by white-space like English, but words In Korean Is a little different in structure from those in English. Words in English generally consist of one word, but those in Korean are composed of one word and/or morpheme or more. Because of this difference, a word between white-spaces is called an Eojeol in Korean. We propose a method for segmenting and classifying Korean words and/or morphemes based on syllables using an instance-based learning. In this paper, elements of feature sets for the instance-based learning are one previous syllable, one current syllable, two next syllables, a final consonant of the current syllable, and two previous categories. Our method shows more than 97% of the F-measure of word segmentation using ETRI corpus and KAIST corpus.
Keywords
Word segmentation; Instance-based learning;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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