Leveraging output term co-occurrence frequencies and latent associations in predicting medical subject headings
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چکیده
منابع مشابه
Leveraging output term co-occurrence frequencies and latent associations in predicting medical subject headings
Trained indexers at the National Library of Medicine (NLM) manually tag each biomedical abstract with the most suitable terms from the Medical Subject Headings (MeSH) terminology to be indexed by their PubMed information system. MeSH has over 26,000 terms and indexers look at each article's full text while assigning the terms. Recent automated attempts focused on using the article title and abs...
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Ontologies such as the Medical Subject Headings (MeSH) and the Gene Ontology (GO) play a major role in biology and medicine since they facilitate data integration and the consistent exchange of information between different entities. They can also be used to index and annotate data and literature, thus enabling efficient search and analysis. Unfortunately, maintaining the ontologies manually is...
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Librarians at the National Library of Medicine tag each biomedical abstract to be indexed by their Pubmed information system with terms from the Medical Subject Headings (MeSH) terminology. The MeSH terminology has over 26,000 terms and indexers look at each article's full text to assign a set of most suitable terms for indexing it. Several recent automated attempts focused on using the article...
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ژورنال
عنوان ژورنال: Data & Knowledge Engineering
سال: 2014
ISSN: 0169-023X
DOI: 10.1016/j.datak.2014.09.002