Transaction databases, Frequent Itemsets, and Their Condensed Representations
In: KDID 2005, 3 Oct 2005, Porto, Portugal.
Mining frequent itemsets is a fundamental task in data mining.
Unfortunately the number of frequent itemsets describing the data
is often too large to comprehend. This problem has been attacked by
condensed representations of frequent itemsets that are subcollections of
frequent itemsets containing only the frequent itemsets that cannot be
deduced from other frequent itemsets in the subcollection, using some
deduction rules. In this paper we review the most popular condensed
representations of frequent itemsets, study their relationship to transaction
databases and each other, examine their combinatorial and computational
complexity, and describe their relationship to other important
concepts in combinatorial data analysis, such as Vapnik-Chervonenkis
dimension and hypergraph transversals.