基于双语语义词典的单字词提取方法

Hongying Zan, Guocheng Duan, Minghong Fan
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引用次数: 1

摘要

现有的术语自动识别方法包括:基于字典的、基于规则的、统计的等。首先,本文简要讨论了基于字典的方法。在此基础上,提出了一种基于字典和基于种子知识相结合的中文单字词提取方法。我们的方法基于两个资源。一个是中文概念词典,这是一个通用的双语语义词典;另一个是从香港法律双语词汇中提取的双语种子集。方法是识别特定于法律领域的术语。我们的方法是将通用语义词典应用于特定领域的术语提取。实验结果表明,该方法在法律领域具有较高的精度。关键词:术语自动识别,双语种子集,汉语概念词典,法律术语,单字术语。
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Single Word Term Extraction Using a Bilingual Semantic Lexicon-Based Approach
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.
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