Word Space
Abstract
Representations for semantic information about words are neces(cid:173) sary 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 num(cid:173) ber of words (50,000) from lexical coccurrence statistics by means of a large-scale linear regression. The representations are success(cid:173) fully applied to word sense disambiguation using a nearest neighbor method .
Cite
Text
Schütze. "Word Space." Neural Information Processing Systems, 1992.Markdown
[Schütze. "Word Space." Neural Information Processing Systems, 1992.](https://mlanthology.org/neurips/1992/schutze1992neurips-word/)BibTeX
@inproceedings{schutze1992neurips-word,
title = {{Word Space}},
author = {Schütze, Hinrich},
booktitle = {Neural Information Processing Systems},
year = {1992},
pages = {895-902},
url = {https://mlanthology.org/neurips/1992/schutze1992neurips-word/}
}