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A syllable based word recognition model for Korean noun extraction
Do Gil Lee
, Hae-Chang Rim
,
Heui Seok Lim
Research output
:
Contribution to journal
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Conference article
›
peer-review
5
Citations (Scopus)
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Dive into the research topics of 'A syllable based word recognition model for Korean noun extraction'. Together they form a unique fingerprint.
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Keyphrases
Word Recognition Models
100%
Nouns Extraction
100%
Part-of
75%
Linguistic Knowledge
50%
System Use
25%
Dictionary
25%
Information Retrieval
25%
Extraction Methods
25%
Tag Sequence
25%
Statistical Information
25%
Morphological Analysis
25%
Morpheme
25%
Information Extraction
25%
Word Boundaries
25%
NLP Applications
25%
Morphosyntax
25%
Most Probable
25%
Extraction System
25%
Morphological Analyzer
25%
Speech Tagging
25%
Tagged Corpus
25%
Text Information
25%
Automatic Text Classification
25%
Rule Rule
25%
Morphological Rules
25%
Computer Science
Experimental Result
100%
Text Classification
100%
Statistical Information
100%
Information Extraction
100%
Morphological Analysis
100%
Text Information
100%
Parts Of Speech Tagging
100%
Information Retrieval
100%
Arts and Humanities
Nouns
100%
Part of speech
40%
Tag
40%
Linguistic Knowledge
40%
Experimental
20%
Morpheme
20%
Corpus
20%
Statistical Information
20%
Morphology
20%
Natural Language Processing
20%
Part-of-speech tagging
20%
morphological rules
20%
Morphological Analysis
20%