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» A native extension of SQL for mining data streams
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ADC
2008
Springer
156views Database» more  ADC 2008»
14 years 1 months ago
Interactive Mining of Frequent Itemsets over Arbitrary Time Intervals in a Data Stream
Mining frequent patterns in a data stream is very challenging for the high complexity of managing patterns with bounded memory against the unbounded data. While many approaches as...
Ming-Yen Lin, Sue-Chen Hsueh, Sheng-Kun Hwang
KDD
2006
ACM
198views Data Mining» more  KDD 2006»
14 years 7 months ago
CFI-Stream: mining closed frequent itemsets in data streams
Mining frequent closed itemsets provides complete and condensed information for non-redundant association rules generation. Extensive studies have been done on mining frequent clo...
Nan Jiang, Le Gruenwald
DASFAA
2010
IEEE
225views Database» more  DASFAA 2010»
13 years 7 months ago
Mining Regular Patterns in Data Streams
Discovering interesting patterns from high-speed data streams is a challenging problem in data mining. Recently, the support metric-based frequent pattern mining from data stream h...
Syed Khairuzzaman Tanbeer, Chowdhury Farhan Ahmed,...
ICDM
2006
IEEE
139views Data Mining» more  ICDM 2006»
14 years 1 months ago
Unsupervised Clustering In Streaming Data
Tools for automatically clustering streaming data are becoming increasingly important as data acquisition technology continues to advance. In this paper we present an extension of...
Dimitris K. Tasoulis, Niall M. Adams, David J. Han...
ICDE
1995
IEEE
139views Database» more  ICDE 1995»
14 years 8 months ago
Set-Oriented Mining for Association Rules in Relational Databases
We describe set-oriented algorithms for mining association rules. Such algorithms imply performing multiple joins and may appear to be inherently less escient than special-purpose...
Maurice A. W. Houtsma, Arun N. Swami