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» Mining evolving data streams for frequent patterns
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DATAMINE
2006
230views more  DATAMINE 2006»
13 years 8 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
IEAAIE
2009
Springer
14 years 3 months ago
An Efficient Algorithm for Maintaining Frequent Closed Itemsets over Data Stream
Data mining refers to the process of revealing unknown and potentially useful information from a large database. Frequent itemsets mining is one of the foundational problems in dat...
Show-Jane Yen, Yue-Shi Lee, Cheng-Wei Wu, Chin-Lin...
DAWAK
2004
Springer
14 years 1 months ago
Mining Maximal Frequently Changing Subtree Patterns from XML Documents
Abstract. Due to the dynamic nature of online information, XML documents typically evolve over time. The change of the data values or structures of an XML document may exhibit some...
Ling Chen 0002, Sourav S. Bhowmick, Liang-Tien Chi...
ICDM
2005
IEEE
168views Data Mining» more  ICDM 2005»
14 years 2 months ago
Discovering Frequent Arrangements of Temporal Intervals
In this paper we study a new problem in temporal pattern mining: discovering frequent arrangements of temporal intervals. We assume that the database consists of sequences of even...
Panagiotis Papapetrou, George Kollios, Stan Sclaro...
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...