Word Space

@inproceedings{Schtze1992WordS,
  title={Word Space},
  author={Hinrich Sch{\"u}tze},
  booktitle={NIPS},
  year={1992}
}
Representations for semantic information about words are necessary for many 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 of words (50,000) from lexical coccurrence statistics by means of a large-scale linear regression. The representations are successfully applied to word sense disambiguation using a nearest neighbor method . 
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