Evaluating WordNet-based Measures of Lexical Semantic Relatedness

  title={Evaluating WordNet-based Measures of Lexical Semantic Relatedness},
  author={Alexander Budanitsky and Graeme Hirst},
  journal={Computational Linguistics},
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… 
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