{"title":"基于马尔可夫的自动术语提取","authors":"Zili Zhou, Yanna Wang, Junzhong Gu","doi":"10.1109/FBIE.2008.84","DOIUrl":null,"url":null,"abstract":"This paper presents an automatic term extraction method based on Markov process. The method aims to extract multi-word domain terms from English corpora. The paper proves that the extracting term process is a Markov chain firstly, and then gives the steps of the Markov-based method. In order to evaluate our method, we use a corpus related to computer science got by Web crawlers, and extract domain terms by methods introduced in the paper. The experiment data shows that our method out performs other methods.","PeriodicalId":415908,"journal":{"name":"2008 International Seminar on Future BioMedical Information Engineering","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Markov-Based Automatic Term Extraction\",\"authors\":\"Zili Zhou, Yanna Wang, Junzhong Gu\",\"doi\":\"10.1109/FBIE.2008.84\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an automatic term extraction method based on Markov process. The method aims to extract multi-word domain terms from English corpora. The paper proves that the extracting term process is a Markov chain firstly, and then gives the steps of the Markov-based method. In order to evaluate our method, we use a corpus related to computer science got by Web crawlers, and extract domain terms by methods introduced in the paper. The experiment data shows that our method out performs other methods.\",\"PeriodicalId\":415908,\"journal\":{\"name\":\"2008 International Seminar on Future BioMedical Information Engineering\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 International Seminar on Future BioMedical Information Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FBIE.2008.84\",\"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 Seminar on Future BioMedical Information Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FBIE.2008.84","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper presents an automatic term extraction method based on Markov process. The method aims to extract multi-word domain terms from English corpora. The paper proves that the extracting term process is a Markov chain firstly, and then gives the steps of the Markov-based method. In order to evaluate our method, we use a corpus related to computer science got by Web crawlers, and extract domain terms by methods introduced in the paper. The experiment data shows that our method out performs other methods.