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Prediction of relevant biomedical documents: a human microbiome case study
2015
BioData Mining
Retrieving relevant biomedical literature has become increasingly difficult due to the large volume and rapid growth of biomedical publication. A query to a biomedical retrieval system often retrieves hundreds of results. Since the searcher will not likely consider all of these documents, ranking the documents is important. Ranking by recency, as PubMed does, takes into account only one factor indicating potential relevance. This study explores the use of the searcher's relevance feedback
doi:10.1186/s13040-015-0061-5
pmid:26361503
pmcid:PMC4564977
fatcat:rlm5amsgqvcx5jwjdwxwp7olz4