Title :
ExAnte: a preprocessing method for frequent-pattern mining
Author :
Bonchi, Francesco ; Giannotti, Fosca ; Mazzanti, Alessio ; Pedreschi, Dino
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.
Keywords :
constraint handling; data mining; data reduction; query languages; query processing; ExAnte; constraint-based data mining query language; data reduction; frequent-pattern mining; preprocessing technique; Association rules; Constraint optimization; Data analysis; Data mining; Floods; Frequency; Information filtering; Itemsets; Laboratories; Pattern analysis; constraints; data reduction; frequent-pattern mining; preprocessing;
Journal_Title :
Intelligent Systems, IEEE
DOI :
10.1109/MIS.2005.45