The problem of devising models and algorithms for high-performance Distributed Data Mining has traditionally been of great interest for the Data Mining and Database communities, merged with researchers and scientists from the Distributed Computing area. In addition to this well-known trend, the emerging MapReduce initiative has conferred a new light on research challenges posed by effectively and efficiently supporting Distributed Data Mining in high-performance environments.

Models and Algorithms for High-Performance Distributed Data Mining

CUZZOCREA, Alfredo Massimiliano
2013-01-01

Abstract

The problem of devising models and algorithms for high-performance Distributed Data Mining has traditionally been of great interest for the Data Mining and Database communities, merged with researchers and scientists from the Distributed Computing area. In addition to this well-known trend, the emerging MapReduce initiative has conferred a new light on research challenges posed by effectively and efficiently supporting Distributed Data Mining in high-performance environments.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2853883
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