{"title":"用摘要对生命医学论文进行分类","authors":"T. Yoshida, H. Ohwada","doi":"10.1109/ICSAI.2012.6223506","DOIUrl":null,"url":null,"abstract":"In this paper, we proposed the technique of judging from the abstract whether life medical literature relates to the protein interaction. More specifically,we identified the technical terms by a rule base, and created the feature vector. Then we applied the technique to the data set of BioCreative, and obtained the result which exceeds the existing technique in recall as a result.","PeriodicalId":164945,"journal":{"name":"2012 International Conference on Systems and Informatics (ICSAI2012)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Using abstracts to classify life medicine papers\",\"authors\":\"T. Yoshida, H. Ohwada\",\"doi\":\"10.1109/ICSAI.2012.6223506\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we proposed the technique of judging from the abstract whether life medical literature relates to the protein interaction. More specifically,we identified the technical terms by a rule base, and created the feature vector. Then we applied the technique to the data set of BioCreative, and obtained the result which exceeds the existing technique in recall as a result.\",\"PeriodicalId\":164945,\"journal\":{\"name\":\"2012 International Conference on Systems and Informatics (ICSAI2012)\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-05-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 International Conference on Systems and Informatics (ICSAI2012)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSAI.2012.6223506\",\"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 International Conference on Systems and Informatics (ICSAI2012)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSAI.2012.6223506","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we proposed the technique of judging from the abstract whether life medical literature relates to the protein interaction. More specifically,we identified the technical terms by a rule base, and created the feature vector. Then we applied the technique to the data set of BioCreative, and obtained the result which exceeds the existing technique in recall as a result.
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