{"title":"基于开放语料库的汉语术语提取新方法","authors":"Jianzhou Liu, Xiongkai Shao","doi":"10.1109/IWISA.2010.5473325","DOIUrl":null,"url":null,"abstract":"Automatic Chinese Term Extraction is an important issue in Natural Language Processing. This paper has proposed a new method to extract terms from open corpus. We have used two improved traditional parameters: mutual information and log-likelihood ratio, and have increased the precision of the method to 75.4%. The results of the research indicate that this method is more efficient and robust than previous term-extraction methods.","PeriodicalId":298764,"journal":{"name":"2010 2nd International Workshop on Intelligent Systems and Applications","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A New Method of Extracting Chinese Term Based on Open Corpus\",\"authors\":\"Jianzhou Liu, Xiongkai Shao\",\"doi\":\"10.1109/IWISA.2010.5473325\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Automatic Chinese Term Extraction is an important issue in Natural Language Processing. This paper has proposed a new method to extract terms from open corpus. We have used two improved traditional parameters: mutual information and log-likelihood ratio, and have increased the precision of the method to 75.4%. The results of the research indicate that this method is more efficient and robust than previous term-extraction methods.\",\"PeriodicalId\":298764,\"journal\":{\"name\":\"2010 2nd International Workshop on Intelligent Systems and Applications\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-05-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 2nd International Workshop on Intelligent Systems and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWISA.2010.5473325\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 2nd International Workshop on Intelligent Systems and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWISA.2010.5473325","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A New Method of Extracting Chinese Term Based on Open Corpus
Automatic Chinese Term Extraction is an important issue in Natural Language Processing. This paper has proposed a new method to extract terms from open corpus. We have used two improved traditional parameters: mutual information and log-likelihood ratio, and have increased the precision of the method to 75.4%. The results of the research indicate that this method is more efficient and robust than previous term-extraction methods.
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