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On the use of Bernoulli mixture models for text classification

โœ Scribed by A. Juan; E. Vidal

Publisher
Elsevier Science
Year
2002
Tongue
English
Weight
143 KB
Volume
35
Category
Article
ISSN
0031-3203

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โœฆ Synopsis

Mixture modelling of class-conditional densities is a standard pattern recognition technique. Although most research on mixture models has concentrated on mixtures for continuous data, emerging pattern recognition applications demand extending research e orts to other data types. This paper focuses on the application of mixtures of multivariate Bernoulli distributions to binary data. More concretely, a text classiรฟcation task aimed at improving language modelling for machine translation is considered.

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