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121
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ADC
2006
Springer
169views Database» more  ADC 2006»
15 years 9 months ago
A further study in the data partitioning approach for frequent itemsets mining
Frequent itemsets mining is well explored for various data types, and its computational complexity is well understood. Based on our previous work by Nguyen and Orlowska (2005), th...
Son N. Nguyen, Maria E. Orlowska
139
Voted
SDM
2009
SIAM
184views Data Mining» more  SDM 2009»
16 years 20 days ago
DensEst: Density Estimation for Data Mining in High Dimensional Spaces.
Subspace clustering and frequent itemset mining via “stepby-step” algorithms that search the subspace/pattern lattice in a top-down or bottom-up fashion do not scale to large ...
Emmanuel Müller, Ira Assent, Ralph Krieger, S...
118
Voted
AUSDM
2007
Springer
112views Data Mining» more  AUSDM 2007»
15 years 9 months ago
Measuring Data-Driven Ontology Changes using Text Mining
Most current ontology management systems concentrate on detecting usage-driven changes and representing changes formally in order to maintain the consistency. In this paper, we pr...
Majigsuren Enkhsaikhan, Wilson Wong, Wei Liu, Mark...
AUSDM
2007
Springer
110views Data Mining» more  AUSDM 2007»
15 years 9 months ago
Adaptive Spike Detection for Resilient Data Stream Mining
Automated adversarial detection systems can fail when under attack by adversaries. As part of a resilient data stream mining system to reduce the possibility of such failure, adap...
Clifton Phua, Kate Smith-Miles, Vincent C. S. Lee,...
87
Voted
ACSC
2004
IEEE
15 years 7 months ago
Detecting Privacy and Ethical Sensitivity in Data Mining Results
Knowledge discovery allows considerable insight into data. This brings with it the inherent risk that what is inferred may be private or ethically sensitive. The process of genera...
Peter Fule, John F. Roddick