SUGGESTIONS TO EXTRACT ASSOCIATION RULES WITH MULTIDIMENSIONAL DATABASE

Hadi Salih, Hilal; Hassan Hashem, Soukaena; Akram Hassan, Shaimaa

	SUGGESTIONS TO EXTRACT ASSOCIATION RULES WITH MULTIDIMENSIONAL DATABASE
AL-TAQANI
Article 1, Volume 23, Issue 1, 2010, Pages 87-93
Authors
Hilal Hadi Salih; Soukaena Hassan Hashem; Shaimaa Akram Hassan
Abstract
Data mining derives its name from the similarities between searching for valuable information in a large database and mining rocks for a vein of valuable ore. The term data mining is actually misnomer, since mining for gold in rocks is usually called “gold mining” and not “rock mining”, thus by analogy, data mining should have been called “knowledge mining” instead. The more general terms such as Knowledge Discovery in Databases (KDD) describe a more complete process. This research concentrates on one particular aspect to extract the association rules from multidimensional databases by the following: It is proposed to deal with multidimensional database to extract the association rules that is done by dividing the multidimensional database into two databases the first one consists of TIDs and the items, while the second one consists of TIDs and dimensions. Then extracting the frequent itemsets for each one separately, the frequent itemsets for the first one is extracted by the traditional apriori algorithm but for the second one a new algorithm has been proposed for that purpose. The two obtained sets will be combined into one set. Finally applying the association rules generation algorithm to get the final rules of the multidimensional database. Keywords: multidimensional database, association rules algorithm

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