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2006
ACL Anthology

Computing Term Translation Probabilities with Generalized Latent Semantic Analysis

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Computing Term Translation Probabilities with Generalized Latent Semantic Analysis
Term translation probabilities proved an effective method of semantic smoothing in the language modelling approach to information retrieval. We use Generalized Latent Semantic Analysis to compute semantically motivated term and document vectors. Normalized cosine similarity between term vectors is used as term translation probability. Our experiments demonstrate that GLSA-based term translation probabilities capture semantic relations between terms and improve performance on document classification.
Irina Matveeva, Gina-Anne Levow
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2006
Where EACL
Authors Irina Matveeva, Gina-Anne Levow
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