PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Transaction databases, Frequent Itemsets, and Their Condensed Representations
Taneli Mielikäinen
In: KDID 2005, 3 Oct 2005, Porto, Portugal.

Abstract

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.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
Information Retrieval & Textual Information Access
ID Code:1475
Deposited By:Taneli Mielikäinen
Deposited On:22 March 2006