Abstract
Data is growing very fast. Today one can spot business trends, detect environmental changes, predict forthcoming social agendas and combat crime, by analyzing large data sets. However, this so-called ”Big Data” analytics is challenging because they have unprecedentedly large volumes. In this presentation, we describe a new approach based on the recent theory of compressive sensing to address the issue of processing, transporting and storing large data sets of enormous sizes gathered from high-resolution sensors and the Internet.
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© 2012 Springer-Verlag Berlin Heidelberg
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Kung, H.T. (2012). Big Data and Compressive Sensing. In: Parashar, M., Kaushik, D., Rana, O.F., Samtaney, R., Yang, Y., Zomaya, A. (eds) Contemporary Computing. IC3 2012. Communications in Computer and Information Science, vol 306. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32129-0_5
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DOI: https://doi.org/10.1007/978-3-642-32129-0_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32128-3
Online ISBN: 978-3-642-32129-0
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