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<Paper uid="H05-1123">
  <Title>Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing (HLT/EMNLP), pages 979-986, Vancouver, October 2005. c(c)2005 Association for Computational Linguistics A Generalized Framework for Revealing Analogous Themes across Related Topics</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> This work addresses the task of identifying thematic correspondences across sub-corpora focused on different topics. We introduce an unsupervised algorithmic framework based on distributional data clustering, which generalizes previous initial works on this task. The empirical results reveal interesting commonalities of different religions. We evaluate the results through measuring the overlap of our clusters with clusters compiled manually by experts. The tested variants of our framework are shown to outperform alternative methods applicable to the task.</Paragraph>
  </Section>
class="xml-element"></Paper>