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» kDCI: a Multi-Strategy Algorithm for Mining Frequent Sets
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PAKDD
2005
ACM
161views Data Mining» more  PAKDD 2005»
15 years 3 months ago
Online Algorithms for Mining Inter-stream Associations from Large Sensor Networks
We study the problem of mining frequent value sets from a large sensor network. We discuss how sensor stream data could be represented that facilitates efficient online mining and ...
K. K. Loo, Ivy Tong, Ben Kao
SAC
2010
ACM
15 years 2 months ago
Mining interesting sets and rules in relational databases
In this paper we propose a new and elegant approach toward the generalization of frequent itemset mining to the multirelational case. We define relational itemsets that contain i...
Bart Goethals, Wim Le Page, Michael Mampaey
DATAMINE
2006
230views more  DATAMINE 2006»
14 years 9 months ago
Mining top-K frequent itemsets from data streams
Frequent pattern mining on data streams is of interest recently. However, it is not easy for users to determine a proper frequency threshold. It is more reasonable to ask users to ...
Raymond Chi-Wing Wong, Ada Wai-Chee Fu
IDA
2007
Springer
14 years 9 months ago
Approximate mining of frequent patterns on streams
Abstract. This paper introduces a new algorithm for approximate mining of frequent patterns from streams of transactions using a limited amount of memory. The proposed algorithm co...
Claudio Silvestri, Salvatore Orlando
93
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ICDM
2007
IEEE
169views Data Mining» more  ICDM 2007»
15 years 1 months ago
Efficient Discovery of Frequent Approximate Sequential Patterns
We propose an efficient algorithm for mining frequent approximate sequential patterns under the Hamming distance model. Our algorithm gains its efficiency by adopting a "brea...
Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu