A method of recognizing the root of an improved dependency tree for the Chinese patent literature

Yun Zhu, Yaohong Jin
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引用次数: 2

Abstract

Compared with ordinary text, patent text in Chinese often has more complex sentence structure and more ambiguity of multiple verbs, which brings more difficulties in patent machine translation. To deal with these problems, this paper presents an improved dependency tree and a method to recognize the root of this tree for Chinese-English patent machine translation. Based on the theory of Hierarchical Network of Concepts (the HNC theory), some semantic features are used in the recognition. Experiments show that the precision of the recognition is close to 85%.
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中文专利文献依赖树根的一种改进识别方法
与普通文本相比,中文专利文本往往句子结构更复杂,多个动词歧义更多,这给专利机器翻译带来了更多的困难。针对这些问题,本文提出了一种改进的依存树及其根的识别方法,用于汉英专利机器翻译。基于层次概念网络理论(HNC理论),利用语义特征进行识别。实验表明,该方法的识别准确率接近85%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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