Development and evaluation of a triple parser to enable visual searching with a biomedical search engine

Myungjae Kwak, Gondy Augusta Leroy, Mikyung Kim

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

We describe a new biomedical search engine that enables visual searching and utilises predicates instead of phrases. We report on the development and evaluation of the triple parser, the most essential component of the search engine, which extracts the necessary predicates from the biomedical text. Using texts from three biomedical related sites (N = 180), we compared the parser's output with a gold standard independently created by a medical expert. The parser achieved more than 91% precision and recall. Its individual components showed different strengths with Finite State Automata being excellent for achieving high recall, while Support Vector Machines improved the precision.

Original languageEnglish (US)
Pages (from-to)351-367
Number of pages17
JournalInternational Journal of Biomedical Engineering and Technology
Volume10
Issue number4
DOIs
StatePublished - Jan 1 2012
Externally publishedYes

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Keywords

  • Finite State Automata
  • Kernel methods
  • Search engine
  • Support Vector Machines
  • Text mining
  • Triple

ASJC Scopus subject areas

  • Biomedical Engineering

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