A Semantic Similarity Framework Exploiting Multiple Parts-of Speech

نویسندگان

  • Giuseppe Pirrò
  • Jérôme Euzenat
چکیده

Semantic similarity aims at establishing resemblance by interpreting the meaning of the objects being compared. The Semantic Web can benefit from semantic similarity in several ways: ontology alignment and merging, automatic ontology construction, semantic-search, to cite a few. Current approaches mostly focus on computing similarity between nouns. The aim of this paper is to define a framework to compute semantic similarity even for other grammar categories such as verbs, adverbs and adjectives. The framework has been implemented on top of WordNet. Extensive experiments confirmed the suitability of this approach in the task of solving English tests.

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تاریخ انتشار 2010