@article{Budanitsky1,
  author = "Alexander Budanitsky and Graeme Hirst",
  title = "Evaluating WordNet-based measures of semantic distance",
  journal = "Computational Linguistics",
  volume = "32",
  number = "1",
  month = "March",
  year = "2006",
  pages = "13--47",
  abstract = "The quantification of lexical semantic relatedness has many
              applications in NLP, and many different measures have been proposed.
              We evaluate five of these measures, all of which use WordNet as their
              central resource, by comparing their performance in detecting and
              correcting real-word spelling errors.  An information-content--based
              measure proposed by Jiang and Conrath is found superior to those
              proposed by Hirst and St-Onge, Leacock and Chodorow, Lin, and Resnik.
              In addition, we explain why distributional similarity is not an
              adequate proxy for lexical semantic relatedness.",
   download = "http://ftp.cs.toronto.edu/pub/gh/Budanitsky+Hirst-2006.pdf"
}