DocumentCode :
1600963
Title :
Single Word Term Extraction Using a Bilingual Semantic Lexicon-Based Approach
Author :
Zan, Hongying ; Duan, Guocheng ; Fan, Ming
Author_Institution :
Zhengzhou Univ., Zhengzhou
Volume :
5
fYear :
2007
Firstpage :
451
Lastpage :
456
Abstract :
The existing approaches to automatic term recognition include these types: dictionary-based, rule-based, statistical, etc. First, we discuss the dictionary-based methods briefly in this paper. Then we propose an approach for Chinese single word term extraction combining the dictionary-based method with seed knowledge-based method. Our method is based on two resources. One is the Chinese concept dictionary which is a general bilingual semantic lexicon and the other one is the bilingual seeds set extracted from a bilingual glossary of HK law. The approach is to recognize the legal domain-specific term. Our approach is applying general semantic lexicon for domain-specific term extraction. The experimental results show that our approach can get high precision in legal field. Keywords: automatic term recognition, bilingual seeds set, Chinese concept dictionary, legal terminology, single word term.
Keywords :
dictionaries; glossaries; natural language processing; text analysis; word processing; Chinese single word term extraction; automatic term recognition; bilingual glossary; bilingual semantic lexicon; dictionary-based methods; Charge coupled devices; Data mining; Dictionaries; Educational institutions; Law; Legal factors; Natural languages; Pattern matching; Statistical analysis; Terminology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
Type :
conf
DOI :
10.1109/ICNC.2007.667
Filename :
4344883
Link To Document :
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