Word Space

Representations for semantic information about words are necessary formany applications of neural networks in natural language processing. This paper describes an efficient, corpus-based method for inducing distributed semantic representations for a large number ofwords (50,000) from lexical coccurrence statistics by means of a large-scale linear regression. The representations are successfully appliedto word sense disambiguation using a nearest neighbor method. 1 Introduction Many tasks in natural language processing require access to semantic information about lexical items and text segments.