Thursday, April 22, 2010

DATA WAREHOUSING &MINING

Abstract


Finding frequent item sets is one of the most investigated fields of data mining. The a priori algorithm is the most established algorithm for
Frequent item sets mining (FIM). Several implementations of the a priori algorithm have been reported and evaluated. One of the implementations
optimizing the data structure with a trie by Bodon catches our attention. The results of the Bodon’s implementation for finding frequent item sets appear to
be faster than the ones by Borgelt and Goethals. In this paper, we revised Bodon’s implementation into a parallel one where input transactions are read by a parallel computer. The effect a parallel computer on this modified implementation is presented.


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