Our main research objective is to define a data mining query language, supported by a system that can optimize constraint-based data mining queries. We have invented ExAnte, a simple yet effective preprocessing technique for frequent-pattern mining. ExAnte exploits constraints to dramatically reduce the analyzed data to those containing patterns of interest. This data reduction, in turn, induces a strong reduction of the candidate patterns' search space, thus supporting substantial performance improvements in subsequent mining.

ExAnte: a Preprocessing Method for Frequent Pattern Mining

GIANNOTTI, FOSCA;PEDRESCHI, DINO
2005-01-01

Abstract

Our main research objective is to define a data mining query language, supported by a system that can optimize constraint-based data mining queries. We have invented ExAnte, a simple yet effective preprocessing technique for frequent-pattern mining. ExAnte exploits constraints to dramatically reduce the analyzed data to those containing patterns of interest. This data reduction, in turn, induces a strong reduction of the candidate patterns' search space, thus supporting substantial performance improvements in subsequent mining.
2005
F., Bonchi; Giannotti, Fosca; A., Mazzanti; Pedreschi, Dino
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/92202
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