PubMed smarter: Query expansion with implicit words based on gene ontology

  • Huang Y
  • Hsu C
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The biomedical literature is increasing rapidly, but most information retrieval systems for biomedicine are not what we really expect. In general, users suffer from exactly specifying what they want to the information retrieval systems, thereby getting back unsatisfied results from these systems. In this paper, we proposed PubMed Smarter that improves the effectiveness of information retrieval in PubMed. We built the word-relationship tree for biomedicine used to find implicit words. The implicit words are the ones correlative to a user query, and facilitate searching the PubMed database. Finally, we also used a fair assessment to evaluate the effectiveness of the system. © 2008 Elsevier B.V. All rights reserved.

Author-supplied keywords

  • Gene ontology
  • IDF
  • Inverse Document Frequency
  • TF
  • Term Frequency
  • Text mining

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  • Yin Fu Huang

  • Chun Hao Hsu

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