Efficient Vertical Mining of Frequent Closed Itemsets and Generators

Laszlo Szathmary 1, * Petko Valtchev 1 Amedeo Napoli 2
* Corresponding author
2 ORPAILLEUR - Knowledge representation, reasonning
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : The effective construction of many association rule bases require 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 is knowingly superior. Hence, we address here the depth-first FCI/FG-mining. The proposed algorithm, Touch, deals with both tasks separately, i.e., uses a well-known vertical method, Charm, to extract FCIs and a novel one called Talky-G, to extract FGs. The respective outputs are matched in a post-processing step. Experimental results indicate that Touch is highly efficient and outperforms its levelwise competitors.
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Laszlo Szathmary, Petko Valtchev, Amedeo Napoli. Efficient Vertical Mining of Frequent Closed Itemsets and Generators. [Research Report] 2009, pp.16. ⟨inria-00371193⟩

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