{"title":"中文多词术语自动抽取","authors":"Narisong, Zhiwei Feng, C. Kit","doi":"10.1109/ALPIT.2008.111","DOIUrl":null,"url":null,"abstract":"We present a new method that extracts multi-word terms through two steps. As input, our technique requires only part of speech tagged texts and a handful of seed words. We use an automatic learning algorithm to select the best extraction single-word terms and take these extraction results of single-word terms as term parts of the multi-word terms to extraction the multi-word terms, the experiment obtains the very well result.","PeriodicalId":169222,"journal":{"name":"2008 International Conference on Advanced Language Processing and Web Information Technology","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Automatic Chinese Multi-word Term Extraction\",\"authors\":\"Narisong, Zhiwei Feng, C. Kit\",\"doi\":\"10.1109/ALPIT.2008.111\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a new method that extracts multi-word terms through two steps. As input, our technique requires only part of speech tagged texts and a handful of seed words. We use an automatic learning algorithm to select the best extraction single-word terms and take these extraction results of single-word terms as term parts of the multi-word terms to extraction the multi-word terms, the experiment obtains the very well result.\",\"PeriodicalId\":169222,\"journal\":{\"name\":\"2008 International Conference on Advanced Language Processing and Web Information Technology\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-07-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 International Conference on Advanced Language Processing and Web Information Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ALPIT.2008.111\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Conference on Advanced Language Processing and Web Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ALPIT.2008.111","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We present a new method that extracts multi-word terms through two steps. As input, our technique requires only part of speech tagged texts and a handful of seed words. We use an automatic learning algorithm to select the best extraction single-word terms and take these extraction results of single-word terms as term parts of the multi-word terms to extraction the multi-word terms, the experiment obtains the very well result.