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        <title>Using Random Indexing to improve Singular Value Decomposition for Latent Semantic Analysis</title>
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            <title>Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC’08)</title>
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            <namePart type="given">Nicoletta</namePart>
            <namePart type="family">Calzolari</namePart>
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            <namePart type="given">Jan</namePart>
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    <abstract>In this paper we present results from using Random indexing for Latent Semantic Analysis to handle Singular Value Decomposition tractability issues. In the paper we compare Latent Semantic Analysis, Random Indexing and Latent Semantic Analysis on Random Indexing reduced matrices. Our results show that Latent Semantic Analysis on Random Indexing reduced matrices provide better results on Precision and Recall than Random Indexing only. Furthermore, computation time for Singular Value Decomposition on a Random indexing reduced matrix is almost halved compared to Latent Semantic Analysis.</abstract>
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%0 Conference Proceedings
%T Using Random Indexing to improve Singular Value Decomposition for Latent Semantic Analysis
%A Sellberg, Linus
%A Jönsson, Arne
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Piperidis, Stelios
%Y Tapias, Daniel
%S Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC’08)
%D 2008
%8 May
%I European Language Resources Association (ELRA)
%C Marrakech, Morocco
%F sellberg-jonsson-2008-using
%X In this paper we present results from using Random indexing for Latent Semantic Analysis to handle Singular Value Decomposition tractability issues. In the paper we compare Latent Semantic Analysis, Random Indexing and Latent Semantic Analysis on Random Indexing reduced matrices. Our results show that Latent Semantic Analysis on Random Indexing reduced matrices provide better results on Precision and Recall than Random Indexing only. Furthermore, computation time for Singular Value Decomposition on a Random indexing reduced matrix is almost halved compared to Latent Semantic Analysis.
%U http://www.lrec-conf.org/proceedings/lrec2008/pdf/586_paper.pdf

Markdown (Informal)

[Using Random Indexing to improve Singular Value Decomposition for Latent Semantic Analysis](http://www.lrec-conf.org/proceedings/lrec2008/pdf/586_paper.pdf) (Sellberg & Jönsson, LREC 2008)

• Using Random Indexing to improve Singular Value Decomposition for Latent Semantic Analysis (Sellberg & Jönsson, LREC 2008)

ACL

• Linus Sellberg and Arne Jönsson. 2008. Using Random Indexing to improve Singular Value Decomposition for Latent Semantic Analysis. In Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08), Marrakech, Morocco. European Language Resources Association (ELRA).