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» A Framework for Mining Association Rules in Data Warehouses
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KDD
2002
ACM
140views Data Mining» more  KDD 2002»
14 years 9 months ago
Mining frequent item sets by opportunistic projection
In this paper, we present a novel algorithm OpportuneProject for mining complete set of frequent item sets by projecting databases to grow a frequent item set tree. Our algorithm ...
Junqiang Liu, Yunhe Pan, Ke Wang, Jiawei Han
SDM
2009
SIAM
170views Data Mining» more  SDM 2009»
14 years 5 months ago
Mining Complex Spatio-Temporal Sequence Patterns.
Mining sequential movement patterns describing group behaviour in potentially streaming spatio-temporal data sets is a challenging problem. Movements are typically noisy and often...
Florian Verhein
ICDM
2007
IEEE
197views Data Mining» more  ICDM 2007»
14 years 2 months ago
Trend Motif: A Graph Mining Approach for Analysis of Dynamic Complex Networks
Complex networks have been used successfully in scientific disciplines ranging from sociology to microbiology to describe systems of interacting units. Until recently, studies of...
Ruoming Jin, Scott McCallen, Eivind Almaas
ICDM
2005
IEEE
150views Data Mining» more  ICDM 2005»
14 years 2 months ago
Combining Multiple Clusterings by Soft Correspondence
Combining multiple clusterings arises in various important data mining scenarios. However, finding a consensus clustering from multiple clusterings is a challenging task because ...
Bo Long, Zhongfei (Mark) Zhang, Philip S. Yu
KDD
2008
ACM
138views Data Mining» more  KDD 2008»
14 years 9 months ago
Quantitative evaluation of approximate frequent pattern mining algorithms
Traditional association mining algorithms use a strict definition of support that requires every item in a frequent itemset to occur in each supporting transaction. In real-life d...
Rohit Gupta, Gang Fang, Blayne Field, Michael Stei...