Abstract
This paper proposes an algorithm for mining frequent closed itemsets from multidimensional databases. The algorithm, which does not require transforming a database into a transaction database, is based on the intersections of object identifications for fast computing the supports of itemsets. Experimental results show that the algorithm is faster than dCHARM when transformation of multidimensional databases into transaction databases is included.
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Schedule a callMore From: International Journal of Computational Vision and Robotics
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