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Numerical linear algebra in data mining
Linköping University, The Institute of Technology. Linköping University, Department of Mathematics, Scientific Computing.ORCID iD: 0000-0003-2281-856X
2006 (English)In: Acta Numerica, ISSN 0962-4929, E-ISSN 1474-0508, Vol. 15, 327-384 p.Article, review/survey (Refereed) Published
Abstract [en]

Ideas and algorithms from numerical linear algebra are important in several areas of data mining. We give an overview of linear algebra methods in text mining (information retrieval), pattern recognition (classification of handwritten digits), and Page Rank computations for web search engines. The emphasis is on rank reduction as a method of extracting information from a data matrix, low-rank approximation of matrices using the singular value decomposition and clustering, and on eigenvalue methods for network analysis. © Cambridge University Press, 2006.

Place, publisher, year, edition, pages
2006. Vol. 15, 327-384 p.
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Engineering and Technology
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URN: urn:nbn:se:liu:diva-50230DOI: 10.1017/S0962492906240017OAI: oai:DiVA.org:liu-50230DiVA: diva2:271126
Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2017-12-12

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Elden, Lars

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