Bridging the gap: Incorporating a semantic similarity measure for effectively mapping PubMed queries to documents.

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第一作者： Sun,Kim

第一单位： National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA. Electronic address: sun.kim@nih.gov.

作者： Sun,Kim ^[1] ; Nicolas,Fiorini ^[2] ; W John,Wilbur ^[3] ; Zhiyong,Lu ^[4]

作者单位： National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA. Electronic address: sun.kim@nih.gov. ^[1] National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA. Electronic address: nicolas.fiorini@nih.gov. ^[2] National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA. Electronic address: wilbur@ncbi.nlm.nih.gov. ^[3] National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA. Electronic address: zhiyong.lu@nih.gov. ^[4]

关键词 Learning to rank PubMed literature search Semantic similarity Word Mover’s Distance Word embeddings

主题词信息存储和检索(Information Storage and Retrieval);PubMed(PubMed);语义学(Semantics)

DOI 10.1016/j.jbi.2017.09.014

PMID 28986328

发布时间 2019-10-08

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准确一般字义偏差语意偏离译文作用小提交