An Efficient Hybrid Algorithm for Mining Frequent Closures and Generators

Laszlo Szathmary (1) , Petko Valtchev (1) , Amedeo Napoli (2) , Robert Godin (1)

1 LATECE Laboratory - UQAM Montreal - Laboratory for Research on Technology for ECommerce
2 ORPAILLEUR - Knowledge representation, reasonning

The effective construction of many association rule bases requires the computation of both frequent closed and frequent generator itemsets (FCIs/FGs). However, these two tasks are rarely combined. Most of the existing solutions apply levelwise breadth-first traversal, though depth-first traversal, depending on data characteristics, is often superior. Hence, we address here a hybrid algorithm that combines the two different traversals. The proposed algorithm, Eclat-Z, extracts frequent itemsets (FIs) in a depth-first way. Then, the algorithm filters FCIs and FGs among FIs in a levelwise manner, and associates the generators to their closures. In Eclat-Z we present a generic technique for extending an arbitrary FI-miner algorithm in order to support the generation of minimal non-redundant association rules too. Experimental results indicate that Eclat-Z outperforms pure levelwise methods in most cases.

Mots clés: itemset extraction; association rule extraction; frequent itemsets; frequent closed itemsets; frequent generators; data mining; knowledge discovery in databases (KDD); algorithms

Domaines: Recherche d'information [cs.IR]

Laszlo Szathmary, Petko Valtchev, Amedeo Napoli, Robert Godin. An Efficient Hybrid Algorithm for Mining Frequent Closures and Generators. 6th International Conference on Concept Lattices and Their Applications (CLA '08), Palacky University (Olomouc) and State University of New York (Binghampton), Oct 2008, Olomouc, Czech Republic. pp.47-58. ⟨inria-00335247⟩