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KDD
2005
ACM
170views Data Mining» more  KDD 2005»
15 years 11 months ago
Parallel mining of closed sequential patterns
Discovery of sequential patterns is an essential data mining task with broad applications. Among several variations of sequential patterns, closed sequential pattern is the most u...
Shengnan Cong, Jiawei Han, David A. Padua
KDD
2005
ACM
153views Data Mining» more  KDD 2005»
15 years 11 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
109views Data Mining» more  KDD 2004»
15 years 11 months ago
Identifying early buyers from purchase data
Market research has shown that consumers exhibit a variety of different purchasing behaviors; specifically, some tend to purchase products earlier than other consumers. Identifyin...
Paat Rusmevichientong, Shenghuo Zhu, David Selinge...
KDD
2004
ACM
139views Data Mining» more  KDD 2004»
15 years 11 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»
15 years 11 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
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