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<Paper uid="W04-0703">
  <Title>Event Clustering on Streaming News Using Co-Reference Chains and Event Words</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> Event clustering on streaming news aims to group documents by events automatically.</Paragraph>
    <Paragraph position="1"> This paper employs co-reference chains to extract the most representative sentences, and then uses them to select the most informative features for clustering. Due to the long span of events, a fixed threshold approach prohibits the latter documents to be clustered and thus decreases the performance. A dynamic threshold using time decay function and spanning window is proposed. Besides the noun phrases in co-reference chains, event words in each sentence are also introduced to improve the related performance. Two models are proposed. The experimental results show that both event words and co-reference chains are useful on event clustering.</Paragraph>
  </Section>
class="xml-element"></Paper>