{"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}
引用次数: 20
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.
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