Sciweavers

Share
SMC
2007
IEEE

Measuring semantic similarity using wordnet-based context vectors

11 years 7 months ago
Measuring semantic similarity using wordnet-based context vectors
— Semantic relatedness between words or concepts is a fundamental problem in many applications of computational linguistics and artificial intelligence. In this paper, a new measure based on the semantic ontology database WordNet is proposed which combines gloss information of concepts with semantic relationships, and organizes concepts as highdimensional vectors. Other relatedness measures are compared and an experimental evaluation against several benchmark sets of human similarity ratings is presented. The Context Vector measure is shown to have one of the best performances.
Shen Wan, Rafal A. Angryk
Added 04 Jun 2010
Updated 04 Jun 2010
Type Conference
Year 2007
Where SMC
Authors Shen Wan, Rafal A. Angryk
Comments (0)
books