Multi-Prototype Vector-Space Models of Word Meaning
Joseph Reisinger, Raymond J. Mooney · 2010
Current vector-space models of lexical seman-tics create a single “prototype ” vector to rep-resent the meaning of a word. However, due to lexical ambiguity, encoding word mean-ing with a single vector is problematic. This paper presents a method that uses cluster-ing to produce multiple “sense-specific ” vec-tors for each word. This approach provides a context-dependent vector representation of word meaning that naturally accommodates homonymy and polysemy. Experimental com-parisons to human judgements of semantic similarity for both isolated words as well as words in sentential contexts demonstrate the superiority of this approach over both proto-type and exemplar based vector-space models. 1