Extending semantic lexicons using vector space models

Word--context vector space models can be used for measuring the semantic similarity between words based on their contextual distributions across large text collections. In this project we propose to use such models for automatically extending a semantic lexicon, such as a wordnet. The scope could also be restricted to a certain set of classes, say focusing only on emotion words as encoded in for example WordNet-Affect.