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<Paper uid="C94-2169">
  <Title>hesaurus-based Efficient Example Retrieval</Title>
  <Section position="5" start_page="1047" end_page="1047" type="concl">
    <SectionTitle>
4 Concluding Remarks
</SectionTitle>
    <Paragraph position="0"> This paper proposed a novel example retrieval method in example-based NLP, bascd-on generating retrieval queries fl'om similarities. The proposed method is applicable to any other definitions of similarities in example-based NLP, if the following three requirements are satisfied, 1) the similarity is calculated based-on word sense similarities in a thesaurus, 2) the similarity can be defined as a fnnetion of a small number of factors, 3) each factor varies over not too many number of discrete values, or otherwise, continuous values can be transformed into not too many discrete values.</Paragraph>
    <Paragraph position="1">  In this paper, we restrict ourselves to the eases where examples have the same verb as input. However, similarities of verbs have to be considered and the example database has to contain examples of many verbs.</Paragraph>
    <Paragraph position="2"> Constructing sub-thesauri aright be a problem in those eases, and the solution nfight be that all the examples are distributed into several sets of sub-thesauri.</Paragraph>
    <Paragraph position="3"> In applications like case-based reasoning (CBR) and information retrieval (IR), good examples do not necessarily have the greatest similarity and thus content-based indexing methods are more effective. On the other hand, in example-based NLP, usually similarity measure is strictly defined and only the most similar examples are retrieved. The proposed query generation retrieval fits this feature of example-based NLP. The idea of generating retrieval queries from similarities is employed also in several other related fields such as translation aid system (Snmita and Tsutsumi, 1988) and CBR (Shimazu, Kitano and Shibata, 1993).</Paragraph>
    <Paragraph position="4"> Since the tasks of those works are different front ours, their formalizatimm are different from ours.</Paragraph>
  </Section>
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