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Automatic Indexing of Journal Abstracts with Latent Semantic Analysis

  • Joel Robert AdamsEmail author
  • Steven Bedrick
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9283)

Abstract

The BioASQ “Task on Large-Scale Online Biomedical Semantic Indexing” charges participants with assigning semantic tags to biomedical journal abstracts. We present a system that takes as input a biomedical abstract and uses latent semantic analysis to identify similar documents in the MEDLINE database. The system then uses a novel ranking scheme to select a list of MeSH tags from candidates drawn from the most similar documents. Our approach achieved better than baseline performance in both precision and recall. We suggest several possible strategies to improve the system’s performance.

Keywords

Latent Semantic Analysis Bordetella Pertussis Similar Document PubMed Annotation Training Document 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Center for Spoken Language UnderstandingOregon Health and Science UniversityPortlandUSA

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