Resnik Similarity Measure

A Resnik similarity measure is a Node-based Semantic Similarity Measure based on the information content of the least common subsumer.

• AKA: Resnik Similarity, Resnik Lexical Semantic Similarity Measure.
• Context:
  • DAG based on the amount of information content that they share.
  • It is based on an information content measure, such as [math]\displaystyle{ IC(c) = -log(\frac{freq(c)}{maxFreq}) }[/math].
  • …
• Counter-Example(s):
  • Path Distance Similarity.
  • Leacock Chodorow Similarity.
  • Wu-Palmer Similarity.
  • Jiang-Conrath Similarity.
  • Lin Similarity.

See: Semantic Similarity Measure, Semantic Similarity Score, Topological Semantic Similarity Measure. Edge-based Semantic Similarity Measure.

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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: Resnik 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).

1995

• (Resnik, 1995) ⇒ Philip Resnik. (1995). “Using Information Content to Evaluate Semantic Similarity in a Taxonomy.” In: Proceedings of the 14th International Joint Conference on Artificial Intelligence (IJCAI 1995).
  • QUOTE: This paper presents a new measure of semantic similarity in an IS-A taxonomy, based on the notion of information content.

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