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KDD
2006
ACM
109views Data Mining» more  KDD 2006»
14 years 9 months ago
Extracting redundancy-aware top-k patterns
Observed in many applications, there is a potential need of extracting a small set of frequent patterns having not only high significance but also low redundancy. The significance...
Dong Xin, Hong Cheng, Xifeng Yan, Jiawei Han
KDD
2005
ACM
153views Data Mining» more  KDD 2005»
14 years 9 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»
14 years 9 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
KDD
2004
ACM
166views Data Mining» more  KDD 2004»
14 years 9 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
KDD
2002
ACM
127views Data Mining» more  KDD 2002»
14 years 9 months ago
Mining knowledge-sharing sites for viral marketing
Viral marketing takes advantage of networks of influence among customers to inexpensively achieve large changes in behavior. Our research seeks to put it on a firmer footing by mi...
Matthew Richardson, Pedro Domingos
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