<?xml version="1.0" standalone="yes"?>
<Paper uid="H05-1113">
  <Title>Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing (HLT/EMNLP), pages 899-906, Vancouver, October 2005. c(c)2005 Association for Computational Linguistics Measuring the relative compositionality of verb-noun (V-N) collocations by integrating features</Title>
  <Section position="9" start_page="904" end_page="904" type="concl">
    <SectionTitle>
9 Conclusion
</SectionTitle>
    <Paragraph position="0"> In this paper, we proposed some collocation based and contextual features to measure the relative compositionality of MWEs of V-N type. We then integrate the proposed features and the traditional features using a SVM based ranking function to rank the V-N collocations based on their relative compositionality. Our main results are as follows, (1) The properties 'Similarity of the collocation to the verb-form of the object', ' Least mutual information difference with similar collocations' and 'Distributed frequency of object using the verb information' contribute greatly to measuring the relative compositionality of V-N collocations. (2) The correlation between the ranks computed by the SVM based ranking function and the human ranking is significantly better than the correlation between ranking of individual features and human ranking.</Paragraph>
    <Paragraph position="1"> In future, we will evaluate the effectiveness of the techniques developed in this paper for applications like Machine Translation. We will also extend our approach to other types of MWEs and to the MWEs of other languages (work on Hindi is in progress).</Paragraph>
  </Section>
class="xml-element"></Paper>