Jiang-Conrath Similarity Measure

A Jiang-Conrath Similarity Measure is a Node-based Semantic Similarity Measure that is based on information content of the least common subsumer.

• AKA: Jiang-Conrath Similarity, Jiang-Conrath Lexical Semantic Similarity Measure.
• Example(s):
  • …
• Counter-Example(s):
  • Path Distance Similarity.
  • Leacock Chodorow Similarity.
  • Wu-Palmer Similarity.
  • Resnik Similarity.
  • Lin Similarity.

See: Semantic Similarity Measure, Semantic Similarity Score.

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References

2011

• (NLTK - WordNetCorpusReader Module, 2011-Jun-19) ⇒ http://nltk.googlecode.com/svn/trunk/doc/api/nltk.corpus.reader.wordnet.WordNetCorpusReader-class.html
  • QUOTE: Jiang-Conrath Similarity Measure: Return a score denoting how similar two word senses are, based on the Information Content (IC) of the Least Common Subsumer (most specific ancestor node) and that of the two input synsets.

1997

• (Jiang & Conrath, 1997) ⇒ Jay J. Jiang, and David W. Conrath. (1997). “Semantic Similarity Based on Corpus Statistics and Lexical Taxonomy.” In: Proceedings on International Conference on Research in Computational Linguistics (ROCLING X).
  • QUOTE: the proposed measure is a combined approach that inherits the edge-based approach of the edge counting scheme, which is then enhanced by the node-based approach of the information content calculation.

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