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Wavelet-based approximation techniques in database systems

Garofalakis Minos

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Year 2006
Type of Item Peer-Reviewed Journal Publication
Bibliographic Citation M. Garofalakis, "Wavelet-based approximation techniques in database systems", IEEE Signal Process. Mag., vol. 23, no. 6, pp. 54-58, Nov. 2006. doi:10.1109/SP-M.2006.248713
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Several recent studies have demonstrated the effectiveness of the wavelet transform as a tool for approximate query processing over massive relational tables and continuous data streams. The idea is to apply wavelet transform to the input relation to obtain a compact data synopsis that comprises a select small collection of wavelet coefficients. The excellent energy compaction and decorrelation properties of the wavelet transform allow for concise and effective approximate representations that exploit the structure of the data. Furthermore, wavelet transforms can generally be computed in linear time, thus allowing for very efficient algorithms. This paper provides a brief overview of recent work and results on wavelet-based approximation techniques for relational database systems