{"title":"基于词库的查询和基于UMLS的概念索引中的文档扩展:在医学信息检索中的应用","authors":"Diem Thi Hoang Le, J. Chevallet, D. T. Thuy","doi":"10.1109/RIVF.2007.369163","DOIUrl":null,"url":null,"abstract":"UMLS is known as largest thesaurus in biomedical domain constructed by Library National of Medicine. In this paper, we aim to evaluate effect of the exploration of UMLS knowledge in medical domain information retrieval by mapping large text of collection ImageCLEFMed to UMLS concepts, and expanding queries and documents automatically base on semantic relations in the UMLS hierarchy. We get the encouraging result with the best enhancement on MAP of 66% compared to text only retrieval, and 34% compared to conceptual indexing baseline.","PeriodicalId":158887,"journal":{"name":"2007 IEEE International Conference on Research, Innovation and Vision for the Future","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"Thesaurus-based query and document expansion in conceptual indexing with UMLS: Application in medical information retrieval\",\"authors\":\"Diem Thi Hoang Le, J. Chevallet, D. T. Thuy\",\"doi\":\"10.1109/RIVF.2007.369163\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"UMLS is known as largest thesaurus in biomedical domain constructed by Library National of Medicine. In this paper, we aim to evaluate effect of the exploration of UMLS knowledge in medical domain information retrieval by mapping large text of collection ImageCLEFMed to UMLS concepts, and expanding queries and documents automatically base on semantic relations in the UMLS hierarchy. We get the encouraging result with the best enhancement on MAP of 66% compared to text only retrieval, and 34% compared to conceptual indexing baseline.\",\"PeriodicalId\":158887,\"journal\":{\"name\":\"2007 IEEE International Conference on Research, Innovation and Vision for the Future\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-03-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 IEEE International Conference on Research, Innovation and Vision for the Future\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RIVF.2007.369163\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE International Conference on Research, Innovation and Vision for the Future","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RIVF.2007.369163","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Thesaurus-based query and document expansion in conceptual indexing with UMLS: Application in medical information retrieval
UMLS is known as largest thesaurus in biomedical domain constructed by Library National of Medicine. In this paper, we aim to evaluate effect of the exploration of UMLS knowledge in medical domain information retrieval by mapping large text of collection ImageCLEFMed to UMLS concepts, and expanding queries and documents automatically base on semantic relations in the UMLS hierarchy. We get the encouraging result with the best enhancement on MAP of 66% compared to text only retrieval, and 34% compared to conceptual indexing baseline.
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