@mastersthesis{ Baron2,
  author = "Faye Baron",
  title = "{Identifying non-compositional idioms in text using WordNet synsets}",
  year = "2007",
  school = "Department of Computer Science, University of Toronto",
  abstract = "<p>Any natural language processing system that does not have a knowledge of non-compositional
             idioms and their interpretation will make mistakes. Previous authors have attempted to
             automatically identify these expressions through the property of non-substitutability:
             similar words cannot be successfully substituted for words in non-compositional idiom
             expressions without changing their meaning.</p>
             <p>In this study, we use the non-substitutability property of idioms to contrast and expand
             the ideas of previous works, drawing on WordNet for the attempted substitutions.
             We attempt to determine the best way to automatically identify idioms through the comparison
             of algorithms including frequency counts, pointwise mutual information and PMI
             ranges; the evaluation of the importance of relative word position; and the assessment of
             the usefulness of syntactic relations. We discover that many of the techniques which we
             try are not useful for identifying idioms and confirm that non-compositionality doesn't appear to 
             be a necessary or sufficient condition for idiomaticity. </p> ",
  download = "http://ftp.cs.toronto.edu/pub/gh/Baron-thesis.pdf"
}