A Hybrid Distributional and Knowledge-based Model of Lexical Semantics
Νικόλαος Αλέτρας, Mark Stevenson · 2015
A range of approaches to the representation of lexical semantics have been explored within Computational Linguistics. Two of the most popular are distributional and knowledge-based models. This paper proposes hybrid models of lexical semantics that combine the advantages of these two approaches. Our models provide robust representations of synony-mous words derived from WordNet. We also make use of WordNet’s hierarcy to refine the synset vectors. The models are evaluated on two widely explored tasks involving lexical semantics: lexical similarity and Word Sense Disambiguation. The hybrid models are found to perform better than standard distributional models and have the additional benefit of modelling polysemy.