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<Paper uid="X98-1018">
  <Title>DYNAMIC DATA FUSION</Title>
  <Section position="2" start_page="0" end_page="0" type="intro">
    <SectionTitle>
INTRODUCTION
</SectionTitle>
    <Paragraph position="0"> Information retrieval researchers have long appreciated the value of combining, or ffilsing, multiple retrieval systems' relevance scores for a set of documents to improve retrieval performance.</Paragraph>
    <Paragraph position="1"> However, it is only recently that researchers have begun to consider adjusting the score fusion method to the user's topic and initial results. This study explores the value of fusing multiple retrieval systems' scores in a manner that adjusts to: the semantic and syntactic features of the user's natural language query, the various systems' biases toward long or short documents, and the extent to which the scores produced by the multiple systems are statistically independent.</Paragraph>
  </Section>
class="xml-element"></Paper>