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Predicting Medical Subject Headings Based on Abstract Similarity and Citations to MEDLINE Records
2016
Proceedings of the 16th ACM/IEEE-CS on Joint Conference on Digital Libraries - JCDL '16
We describe a classifier-enhanced nearest neighbor approach to assigning Medical Subject Headings (MeSH R ) to unlabeled documents using a combination of abstract similarities and direct citations to labeled MEDLINE records. The approach frames the classification problem by decomposing it into sets of siblings in the MeSH hierarchy (e.g., training a classifier for predicting "Heterocyclic Compounds, 2-Ring" vs. other "Heterocyclic Compounds"). Preliminary experiments using a small but diverse
doi:10.1145/2910896.2910920
dblp:conf/jcdl/KehoeT16
fatcat:utoprlglhfahpfpsvllr2jjpkm