Automatic classification of PubMed abstracts with Latent semantic indexing: Working notes
CLEF 2014 - Working Notes for CLEF 2014 Conference,
Jan 2014
Abstract
The 2014 BioASQ challenge 2a tasks participants with assigning semantic tags to biomedical journal abstracts. We present a system that uses Latent Semantic Analysis to identify semantically similar documents in MEDLINE to an unlabeled abstract, and then uses a novel ranking scheme to select a list of MeSH headers from candidates drawn from the most similar documents. Our approach achieved good precision, but suffered in terms of recall. We describe several possible strategies to improve our system's performance.Add the full text or supplementary notes for the publication here using Markdown formatting.