<?xml version="1.0" standalone="yes"?>
<Paper uid="W00-0403">
  <Title>I I I I I I I I I I I I I I I I I I I Centroid-based summarization of multiple documents: sentence extraction, utility-based evaluation, and user studies</Title>
  <Section position="7" start_page="27" end_page="28" type="evalu">
    <SectionTitle>
6 Contributions and future work
</SectionTitle>
    <Paragraph position="0"> We presented a new multi-document summarizer, MEAD. It summarizes clusters of news articles automatically grouped by a topic detection system.</Paragraph>
    <Paragraph position="1"> MEAD uses information from the centroids of the clusters to select sentences that are most likely to be relevant to the cluster topic.</Paragraph>
    <Paragraph position="2"> We used a new utility-based technique, CBSU, for the evaluation of MEAD and of summarizers in general. We found that MEAD produces summaries that are similar in quality to the ones produced by humans. We also compared MEAD's performance to an alternative method, multi-document lead, and  showed how MEAD's sentence scoring weights can be modified to produce summaries significantly better than the alternatives.</Paragraph>
    <Paragraph position="3"> We also looked at a property of multi-document chisters, namely cross-sentence information subsumption (which is related to the MMR metric proposed in \[Carbonell and Goldstein, 1998\]) and showed how it can be used in evaluating multi-document summaries.</Paragraph>
    <Paragraph position="4"> All our findings are backed by the analysis of two experiments that we performed with human subjects. We found that the interjudge agreement on sentence utility is very high while the agreement on cross-sentence subsumption is moderately low, although promising.</Paragraph>
    <Paragraph position="5"> In the future, we would like to test our multidocument summarizer on a larger corpus and improve the summarization algorithm. We would also like to explore how the techniques we proposed here can be used for multiligual multidocument summarization.</Paragraph>
  </Section>
class="xml-element"></Paper>