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<Paper uid="W06-0302">
  <Title>Sydney, July 2006. c(c)2006 Association for Computational Linguistics Toward Opinion Summarization: Linking the Sources</Title>
  <Section position="9" start_page="13" end_page="13" type="concl">
    <SectionTitle>
8 Conclusions
</SectionTitle>
    <Paragraph position="0"> As a first step toward opinion summarization we targeted the problem of source coreference resolution. We showed that the problem can be tackled effectively as noun coreference resolution.</Paragraph>
    <Paragraph position="1"> Oneaspectof sourcecoreferenceresolutionthat we do not address is the use of unsupervised information. The corpus contains many automatically identified non-source NPs, which can be used to benefit source coreference resolution in two ways.</Paragraph>
    <Paragraph position="2"> First, a machine learning approach could use the unlabeleddatatoestimatetheoveralldistributions.</Paragraph>
    <Paragraph position="3"> Second, some links between sources may be realized through a non-source NPs (see the example of figure 1). As a follow-up to the work described in this paper we developed a method that utilizes the unlabeled NPs in the corpus using a structured rule learner (Stoyanov and Cardie, 2006).</Paragraph>
  </Section>
class="xml-element"></Paper>