Single Word Term Extraction Using a Bilingual Semantic Lexicon-Based Approach

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.