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http://dx.doi.org/10.9728/dcs.2016.17.3.203

Functional Expansion of Morphological Analyzer Based on Longest Phrase Matching For Efficient Korean Parsing  

Lee, Hyeon-yoeng (Woosuk University Game & Contents)
Lee, Jong-seok (Woosuk University Game & Contents)
Kang, Byeong-do (Daegu University Computer & Information Technology)
Yang, Seung-weon (Woosuk University Game & Contents)
Publication Information
Journal of Digital Contents Society / v.17, no.3, 2016 , pp. 203-210 More about this Journal
Abstract
Korean is free of omission of sentence elements and modifying scope, so managing it on morphological analyzer is better than parser. In this paper, we propose functional expansion methods of the morphological analyzer to ease the burden of parsing. This method is a longest phrase matching method. When the series of several morpheme have one syntax category by processing of Unknown-words, Compound verbs, Compound nouns, Numbers and Symbols, our method combines them into a syntactic unit. And then, it is to treat by giving them a semantic features as syntax unit. The proposed morphological analysis method removes unnecessary morphological ambiguities and deceases results of morphological analysis, so improves accuracy of tagger and parser. By empirical results, we found that our method deceases 73.4% of Parsing tree and 52.4% of parsing time on average.
Keywords
sentence element; morphological analyzer; longest phrase matching method; parser;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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