{"title":"生物医学路径的知识提取框架。","authors":"Sanda Harabagiu, Cosmin Adrian Bejan","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>In this paper we present a novel knowledge extraction framework that is based on semantic parsing. The semantic information originates in a variety of resources, but one in particular, namely BioFrameNet, is central to the characterization of complex events and processes that form biomedical pathways. The paper discusses the promising results of semantic parsing and explains how these results can be used for capturing complex medical knowledge.</p>","PeriodicalId":89276,"journal":{"name":"Summit on translational bioinformatics","volume":"2010 ","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2010-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041549/pdf/","citationCount":"0","resultStr":"{\"title\":\"A knowledge extraction framework for biomedical pathways.\",\"authors\":\"Sanda Harabagiu, Cosmin Adrian Bejan\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>In this paper we present a novel knowledge extraction framework that is based on semantic parsing. The semantic information originates in a variety of resources, but one in particular, namely BioFrameNet, is central to the characterization of complex events and processes that form biomedical pathways. The paper discusses the promising results of semantic parsing and explains how these results can be used for capturing complex medical knowledge.</p>\",\"PeriodicalId\":89276,\"journal\":{\"name\":\"Summit on translational bioinformatics\",\"volume\":\"2010 \",\"pages\":\"1-5\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041549/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Summit on translational bioinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Summit on translational bioinformatics","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A knowledge extraction framework for biomedical pathways.
In this paper we present a novel knowledge extraction framework that is based on semantic parsing. The semantic information originates in a variety of resources, but one in particular, namely BioFrameNet, is central to the characterization of complex events and processes that form biomedical pathways. The paper discusses the promising results of semantic parsing and explains how these results can be used for capturing complex medical knowledge.
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