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Istituto di Scienza e Tecnologie dell'Informazione     
Ruggieri S. Frequent regular itemset mining. In: KDD'2010 - 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (Washington, DC, 25-28 July 2010). Proceedings, pp. 263 - 272. ACM, 2010.
 
 
Abstract
(English)
Concise representations of frequent itemsets sacrifice readability and direct interpretability by a data analyst of the concise patterns extracted. In this paper, we introduce an extension of itemsets, called regular, with an immediate semantics and interpretability, and a conciseness comparable to closed itemsets. Regular itemsets allow for specifying that an item may or may not be present; that any subset of an itemset may be present; and that any non-empty subset of an itemset may be present. We devise a procedure, called Regular Mine, for mining a set of regular itemsets that is a concise representation of frequent itemsets. The procedure computes a covering, in terms of regular itemsets, of the frequent itemsets in the class of equivalence of a closed one. We report experimental results on several standard dense and sparse datasets that validate the proposed approach. 2010 ACM.
URL: http://dl.acm.org/citation.cfm?doid=1835804.1835840
DOI: 10.1145/1835804.1835840
Subject Closed itemsets
Concise representations
Data analysts
Data sets
Frequent Itemsets
Interpretability
Item sets
Itemset
Itemset mining
H.2.8 Database applications. Data mining


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