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» COFI approach for mining frequent itemsets revisited
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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
91
Voted
KDD
2007
ACM
170views Data Mining» more  KDD 2007»
15 years 10 months ago
From frequent itemsets to semantically meaningful visual patterns
Data mining techniques that are successful in transaction and text data may not be simply applied to image data that contain high-dimensional features and have spatial structures....
Junsong Yuan, Ying Wu, Ming Yang
FIMI
2004
175views Data Mining» more  FIMI 2004»
14 years 11 months ago
CT-PRO: A Bottom-Up Non Recursive Frequent Itemset Mining Algorithm Using Compressed FP-Tree Data Structure
Frequent itemset mining (FIM) is an essential part of association rules mining. Its application for other data mining tasks has also been recognized. It has been an active researc...
Yudho Giri Sucahyo, Raj P. Gopalan
ADC
2008
Springer
156views Database» more  ADC 2008»
15 years 4 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
2000
ACM
118views Data Mining» more  KDD 2000»
15 years 1 months ago
Generating non-redundant association rules
The traditional association rule mining framework produces many redundant rules. The extent of redundancy is a lot larger than previously suspected. We present a new framework for...
Mohammed Javeed Zaki