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

Yun Zhu, Yaohong Jin
{"title":"A method of recognizing the root of an improved dependency tree for the Chinese patent literature","authors":"Yun Zhu, Yaohong Jin","doi":"10.1109/CCIS.2012.6664638","DOIUrl":null,"url":null,"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%.","PeriodicalId":392558,"journal":{"name":"2012 IEEE 2nd International Conference on Cloud Computing and Intelligence Systems","volume":"88 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE 2nd International Conference on Cloud Computing and Intelligence Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCIS.2012.6664638","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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%.
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。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信