Solving total least-squares problems in information retrieval (Q1587280)
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scientific article; zbMATH DE number 1532997
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Solving total least-squares problems in information retrieval |
scientific article; zbMATH DE number 1532997 |
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Solving total least-squares problems in information retrieval (English)
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17 May 2001
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The Riemannian singular value decomposition (R-SVD) is modified and used to formulate an enhanced implementation of latent semantic indexing (LSI) for conceptual information retrieval. A new algorithm for computing the R-SVD is also described. In updating the LSI models, this R-SVD can be very effective. Experiments demonstrate that a 20\% improvement (in retrieval) over the current LSI model is possible.
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information filtering
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numerical experiments
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Riemannian singular value decomposition
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latent semantic indexing
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information retrieval
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algorithm
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