{"title":"中文专利文献依赖树根的一种改进识别方法","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":"{\"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}","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}
A method of recognizing the root of an improved dependency tree for the Chinese patent literature
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%.