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Título:
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Learning task-specific bilexical embeddings
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Autor/a:
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Madhyastha, Pranava S.; Carreras Pérez, Xavier; Quattoni, Ariadna
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Abstract:
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We present a method that learns bilexical operators over distributional representations of words and leverages supervised data for a linguistic relation. The learning algorithm exploits lowrank bilinear forms and induces low-dimensional embeddings of the lexical space tailored for the target linguistic relation. An advantage of imposing low-rank constraints is that prediction
is expressed as the inner-product between low-dimensional embeddings, which can have great computational benefits. In experiments with multiple linguistic bilexical relations we show that our method effectively learns using embeddings of a few dimensions. |
Abstract:
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Peer Reviewed |
Materia(s):
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-Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Llenguatge natural -Computational linguistics -Lingüística computacional |
Derechos:
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Tipo de documento:
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Artículo - Versión publicada Objeto de conferencia |
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