Abstract
The extensive use of Big Data has now become common in plethora of technologies and industries. From massive data bases to business intelligence and datamining applications; from search engines to recommendation systems; advancing the state of the art of voice recognition, translation and more. The design, analysis and engineering of Big Data algorithms has multiple flavors, including massive parallelism, streaming algorithms, sketches and synopses, cloud technologies, and more. We will discuss some of these aspects, and reflect on their evolution and on the interplay between the theory and practice of Big Data algorithmics.
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© 2012 Springer-Verlag Berlin Heidelberg
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Matias, Y. (2012). On Big Data Algorithmics. In: Epstein, L., Ferragina, P. (eds) Algorithms – ESA 2012. ESA 2012. Lecture Notes in Computer Science, vol 7501. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33090-2_1
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DOI: https://doi.org/10.1007/978-3-642-33090-2_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33089-6
Online ISBN: 978-3-642-33090-2
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