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14

NAACL
2010

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Using Gaussian Mixture Models to Detect Figurative Language in Context

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Using Gaussian Mixture Models to Detect Figurative Language in Context

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We present a Gaussian Mixture model for detecting different types of figurative language in context. We show that this model performs well when the parameters are estimated in an unsupervised fashion using EM. Performance can be improved further by estimating the parameters from a small annotated data set.

Linlin Li, Caroline Sporleder

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Computational Linguistics | Gaussian Mixture Model | NAACL 2010 | Small Annotated Data | Unsupervised Fashion |

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Added	14 Feb 2011
Updated	14 Feb 2011
Type	Journal
Year	2010
Where	NAACL
Authors	Linlin Li, Caroline Sporleder

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