|Title||Extraction de connaissances basée sur les arbres Patricia|
|Publication Type||Conference Paper|
|Year of Publication||2006|
|Authors||Ben HajHmida, M|
|Conference Name||African Conference on Research in Computer Science and Applied Mathematics|
|Keywords||Association rules, Closed Itemsets, Data mining, Frequent closed Itemsets, Frequent itemsets|
In the context of knowledge discovery, the association rules mining usually uses frequentitemsets mining technique. But the huge number of itemsets led by the mining of the complete set offrequent itemsets can be reduced to the mining of frequent closed Itemsets. The literature algorithmsproposed for this kind of items have performances that depend on the database density, dense orsparse. In this paper, we propose an algorithm for mining frequent closed itemsets based on Patriciatree structure, that permits to have good performances for the two kinds of database. Experimentalresults show that our algorithm outperforms the similar ones for most of the test databases we used.