Inductive probabilistic taxonomy learning using singular value decomposition

Natural Language Engineering, pp. 71-94, 2011.

Cited by: 8|Bibtex|Views10|DOI:https://doi.org/10.1017/S1351324910000197
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Other Links: dblp.uni-trier.de|dl.acm.org|academic.microsoft.com

Abstract:

Capturing word meaning is one of the challenges of natural language processing (NLP). Formal models of meaning, such as networks of words or concepts, are knowledge repositories used in a variety of applications. To be effectively used, these networks have to be large or, at least, adapted to specific domains. Learning word meaning from t...More

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