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Abstract: 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. (Update)
Context of citations to this paper: More
...to systematically combining information from multiple contextual features in determining the sense of an ambiguous word. Schutze ([26]) derived contextual features from a singular value decomposition of a matrix of letter four gram co occurrence frequencies, thereby...
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BibTeX entry: (Update)
Schutze, H. 1993. Word space. In S. Hanson, J. Cowan, and C. Giles, editors, Advances in Neural Information Processing Systems 5. Morgan Kaufmann Publishers. http://citeseer.ist.psu.edu/schutze93word.html More
@incollection{ schutze93word,
author = "Hinrich Sch{\"u}tze",
title = "Word space",
booktitle = "Advances in Neural Information Processing Systems 5",
editor = "S. Hanson and J. Cowan and C. Giles",
publisher = "Morgan Kaufmann Publishers",
year = "1993",
url = "citeseer.ist.psu.edu/schutze93word.html" }
Citations (may not include all citations):27 A Connectionist Approach to Word Sense Disambiguation (context) - Cottrell - 1989
23 Large-scale sparse singular value computations - Berry - 1992
15 An approach to the automatic construction of global thesauri (context) - Pitman - 1990
1 AutoClass: A Bayesian classification system (context) - models, language et al. - 1988
1 Scatter-gather: A clusterbased approach to browsing large do.. (context) - Processing, -- et al. - 1992
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