File Information
File: 05-lr/acl_arc_1_sum/cleansed_text/xml_by_section/abstr/01/h01-1030_abstr.xml
Size: 975 bytes
Last Modified: 2025-10-06 13:42:01
<?xml version="1.0" standalone="yes"?> <Paper uid="H01-1030"> <Title>First Story Detection using a Composite Document Representation.</Title> <Section position="1" start_page="0" end_page="0" type="abstr"> <SectionTitle> ABSTRACT </SectionTitle> <Paragraph position="0"> In this paper, we explore the effects of data fusion on First Story Detection [1] in a broadcast news domain. The data fusion element of this experiment involves the combination of evidence derived from two distinct representations of document content in a single cluster run. Our composite document representation consists of a concept representation (based on the lexical chains derived from a text) and free text representation (using traditional keyword index terms). Using the TDT1 evaluation methodology we evaluate a number of document representation strategies and propose reasons why our data fusion experiment shows performance improvements in the TDT domain.</Paragraph> </Section> class="xml-element"></Paper>