Word Similarity In WordNet

  title={Word Similarity In WordNet},
  author={Tran Hong-Minh and Dan J. Smith},
We present a new information theoretic approach to measure the semantic similarity between concepts. By exploiting advantages of distance (edge-base) approach for taxonomic tree-like concepts, we enhance the strength of information theoretic (node-based) approach. Our measure therefore gives a complete view of word similarity, which cannot be achieved by solely applying node-based approaches. Our experimental measure achieves 88%, correlating with human rating. 

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