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Proceedings 2001 IEEE International Conference on Data Mining

Average number of frequent (closed) patterns in Bernoulli and Markovian databases

Content Provider	IEEE Xplore Digital Library
Author	Lhote, L. Rioult, F. Soulet, A.
Copyright Year	2005
Description	Author affiliation: GREYC, CNRS - UMR, Univ. de Caen Basse-Normandie, France (Lhote, L.; Rioult, F.; Soulet, A.)
Abstract	In data mining, enumerate the frequent or the closed patterns is often the first difficult task leading to the association rules discovery. The number of these patterns represents a great interest. The lower bound is known to be constant whereas the upper bound is exponential, but both situations correspond to pathological cases. For the first time, we give an average analysis of the number of frequent or closed patterns. Average analysis is often closer to real situations and gives more information about the role of the parameters. In this paper, two probabilistic models are studied: a Bernoulli and a Markovian. In both models and for large databases, we prove that the number of frequent patterns, for a fixed frequency threshold, is exponential in the number of items and polynomial in the number of transactions. On the other hand, for a proportional frequency threshold, the number of frequent patterns is polynomial in the number of items and does not involve the number of transactions. Finally, we prove in the Bernoulli model that the number of closed patterns, for a proportional frequency threshold, is polynomial in the number of items.
File Size	113538
File Format	PDF
ISBN	0769522785
ISSN	15504786
DOI	10.1109/ICDM.2005.31
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-11-27
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data mining Association rules Transaction databases Frequency Polynomials Pathology Upper bound Pattern analysis Information analysis Sampling methods
Content Type	Text
Resource Type	Article

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