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<Paper uid="P06-4005">
  <Title>Sydney, July 2006. c(c)2006 Association for Computational Linguistics An intelligent search engine and GUI-based efficient MEDLINE search tool based on deep syntactic parsing</Title>
  <Section position="3" start_page="0" end_page="0" type="intro">
    <SectionTitle>
1 Introduction
</SectionTitle>
    <Paragraph position="0"> Recently, biomedical researchers have been facing the vast repository of research papers, e.g.</Paragraph>
    <Paragraph position="1"> MEDLINE. These researchers are eager to search biomedical correlations such as protein-protein or gene-disease associations. The use of natural language processing technology is expected to reduce their burden, and various attempts of information extraction using NLP has been being made (Blaschke and Valencia, 2002; Hao et al., 2005; Chun et al., 2006). However, the framework of traditional information retrieval (IR) has difficulty with the accurate retrieval of such relational concepts. This is because relational concepts are essentially determined by semantic relations of words, and keyword-based IR techniques are insufficient to describe such relations precisely.</Paragraph>
    <Paragraph position="2"> This paper proposes a practical HPSG parser for English, Enju, an intelligent search engine for the accurate retrieval of relational concepts from  GENIA corpus MEDLINE, MEDIE, and a GUI-based efficient MEDLINE search tool, Info-PubMed.</Paragraph>
  </Section>
class="xml-element"></Paper>