Informační systém MU
ŘEHŮŘEK, Radim. Subspace Tracking for Latent Semantic Analysis. In Clough, P.; Foley, C.; Gurrin, C.; Jones, G.J.F.; Kraaij, W. (Eds.). Proceedings of the 33rd European Conference on Information Retrieval (ECIR). Heidelberg: Springer, 2011. p. 289-300, 12 pp. ISBN 978-3-642-20160-8. doi:10.1007/978-3-642-20161-5_29.
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Basic information
Original name Subspace Tracking for Latent Semantic Analysis
Authors ŘEHŮŘEK, Radim (203 Czech Republic, guarantor, belonging to the institution).
Edition Heidelberg, Proceedings of the 33rd European Conference on Information Retrieval (ECIR), p. 289-300, 12 pp. 2011.
Publisher Springer
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10000 1. Natural Sciences
Country of publisher Ireland
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
Impact factor Impact factor: 0.402 in 2005
RIV identification code RIV/00216224:14330/11:00067252
Organization unit Faculty of Informatics
ISBN 978-3-642-20160-8
ISSN 0302-9743
UT WoS 000301968000029
Keywords in English scalability svd subspace tracking
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 30/4/2014 04:36.
Modern applications of Latent Semantic Analysis (LSA) must deal with enormous (often practically infinite) data collections, calling for a single-pass matrix decomposition algorithm that operates in constant memory w.r.t. the collection size. This paper introduces a \emph{streamed distributed algorithm for incremental SVD updates}. Apart from the theoretical derivation, we present experiments measuring numerical accuracy and runtime performance of the algorithm over several data collections, one of which is the whole of the English Wikipedia.
LC536, research and development projectName: Centrum komputační lingvistiky
Investor: Ministry of Education, Youth and Sports of the CR, Basic Research Center
Displayed: 6/4/2020 15:03