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KDD
2008
ACM
161views Data Mining» more  KDD 2008»
16 years 6 months ago
Spectral domain-transfer learning
Traditional spectral classification has been proved to be effective in dealing with both labeled and unlabeled data when these data are from the same domain. In many real world ap...
Xiao Ling, Wenyuan Dai, Gui-Rong Xue, Qiang Yang, ...
KDD
2007
ACM
182views Data Mining» more  KDD 2007»
16 years 6 months ago
A fast algorithm for finding frequent episodes in event streams
Frequent episode discovery is a popular framework for mining data available as a long sequence of events. An episode is essentially a short ordered sequence of event types and the...
Srivatsan Laxman, P. S. Sastry, K. P. Unnikrishnan
KDD
2006
ACM
128views Data Mining» more  KDD 2006»
16 years 6 months ago
On privacy preservation against adversarial data mining
Privacy preserving data processing has become an important topic recently because of advances in hardware technology which have lead to widespread proliferation of demographic and...
Charu C. Aggarwal, Jian Pei, Bo Zhang 0002
KDD
2005
ACM
153views Data Mining» more  KDD 2005»
16 years 6 months ago
Using retrieval measures to assess similarity in mining dynamic web clickstreams
While scalable data mining methods are expected to cope with massive Web data, coping with evolving trends in noisy data in a continuous fashion, and without any unnecessary stopp...
Olfa Nasraoui, Cesar Cardona, Carlos Rojas
KDD
2004
ACM
139views Data Mining» more  KDD 2004»
16 years 6 months ago
Learning a complex metabolomic dataset using random forests and support vector machines
Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
Young Truong, Xiaodong Lin, Chris Beecher
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