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IDA
2011
Springer
13 years 9 days ago
A parallel, distributed algorithm for relational frequent pattern discovery from very large data sets
The amount of data produced by ubiquitous computing applications is quickly growing, due to the pervasive presence of small devices endowed with sensing, computing and communicatio...
Annalisa Appice, Michelangelo Ceci, Antonio Turi, ...
DATAMINE
2006
230views more  DATAMINE 2006»
13 years 5 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
ICDM
2005
IEEE
157views Data Mining» more  ICDM 2005»
13 years 11 months ago
Blocking Anonymity Threats Raised by Frequent Itemset Mining
In this paper we study when the disclosure of data mining results represents, per se, a threat to the anonymity of the individuals recorded in the analyzed database. The novelty o...
Maurizio Atzori, Francesco Bonchi, Fosca Giannotti...
LWA
2004
13 years 6 months ago
Efficient Frequent Pattern Mining in Relational Databases
Data mining on large relational databases has gained popularity and its significance is well recognized. However, the performance of SQL based data mining is known to fall behind ...
Xuequn Shang, Kai-Uwe Sattler, Ingolf Geist
IDA
2007
Springer
13 years 5 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