Looking for a structural characterization of the sparseness measure of (frequent closed) itemset contexts

Autor: E. Mephu Nguifo, Tarek Hamrouni, S. Ben Yahia

Publikováno v: Information Sciences
Information Sciences, Elsevier, 2013, 222, pp.343-361. ⟨10.1016/j.ins.2012.08.005⟩
Information Sciences, 2013, 222, pp.343-361. ⟨10.1016/j.ins.2012.08.005⟩

International audience; It is widely recognized that the performances of frequent-pattern mining algorithms are closely dependent on data being handled, i.e., sparse or dense. The same situation applies to the efficiency of concise representations of

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::581a1f488d619b9eb47c199da9317699
https://hal.archives-ouvertes.fr/hal-01299269

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