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» Mining top-K frequent itemsets from data streams
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IDA
2002
Springer
13 years 8 months ago
Optimization of association rule mining queries
Levelwise algorithms (e.g., the Apriori algorithm) have been proved eective for association rule mining from sparse data. However, in many practical applications, the computation ...
Baptiste Jeudy, Jean-François Boulicaut
ICMCS
2006
IEEE
344views Multimedia» more  ICMCS 2006»
14 years 2 months ago
Pattern Mining in Visual Concept Streams
Pattern mining algorithms are often much easier applied than quantitatively assessed. In this paper we address the pattern evaluation problem by looking at both the capability of ...
Lexing Xie, Shih-Fu Chang
PODS
2009
ACM
134views Database» more  PODS 2009»
14 years 9 months ago
An efficient rigorous approach for identifying statistically significant frequent itemsets
As advances in technology allow for the collection, storage, and analysis of vast amounts of data, the task of screening and assessing the significance of discovered patterns is b...
Adam Kirsch, Michael Mitzenmacher, Andrea Pietraca...
CIKM
2009
Springer
14 years 15 days ago
Efficient itemset generator discovery over a stream sliding window
Mining generator patterns has raised great research interest in recent years. The main purpose of mining itemset generators is that they can form equivalence classes together with...
Chuancong Gao, Jianyong Wang
AUSDM
2007
Springer
145views Data Mining» more  AUSDM 2007»
14 years 2 months ago
Discovering Frequent Sets from Data Streams with CPU Constraint
Data streams are usually generated in an online fashion characterized by huge volume, rapid unpredictable rates, and fast changing data characteristics. It has been hence recogniz...
Xuan Hong Dang, Wee Keong Ng, Kok-Leong Ong, Vince...