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» Discovering Frequent Closed Itemsets for Association Rules
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KDD
2002
ACM
214views Data Mining» more  KDD 2002»
14 years 8 months ago
Privacy preserving association rule mining in vertically partitioned data
Privacy considerations often constrain data mining projects. This paper addresses the problem of association rule mining where transactions are distributed across sources. Each si...
Jaideep Vaidya, Chris Clifton
DKE
2007
119views more  DKE 2007»
13 years 7 months ago
Association rules mining using heavy itemsets
A well-known problem that limits the practical usage of association rule mining algorithms is the extremely large number of rules generated. Such a large number of rules makes the...
Girish Keshav Palshikar, Mandar S. Kale, Manoj M. ...
ICCS
2004
Springer
14 years 1 months ago
Iceberg Query Lattices for Datalog
In this paper we study two orthogonal extensions of the classical data mining problem of mining association rules, and show how they naturally interact. The first is the extension...
Gerd Stumme
ICDM
2005
IEEE
139views Data Mining» more  ICDM 2005»
14 years 1 months ago
Approximate Inverse Frequent Itemset Mining: Privacy, Complexity, and Approximation
In order to generate synthetic basket data sets for better benchmark testing, it is important to integrate characteristics from real-life databases into the synthetic basket data ...
Yongge Wang, Xintao Wu
ICDE
2008
IEEE
192views Database» more  ICDE 2008»
14 years 9 months ago
Verifying and Mining Frequent Patterns from Large Windows over Data Streams
Mining frequent itemsets from data streams has proved to be very difficult because of computational complexity and the need for real-time response. In this paper, we introduce a no...
Barzan Mozafari, Hetal Thakkar, Carlo Zaniolo