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KDD
2006
ACM
109views Data Mining» more  KDD 2006»
14 years 10 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
2004
ACM
126views Data Mining» more  KDD 2004»
14 years 10 months ago
High-throughput Protein Interactome Data: Minable or Not?
There is an emerging trend in post-genome biology to study the collection of thousands of protein interaction pairs (protein interactome) derived from high-throughput experiments....
Jake Yue Chen, Andrey Y. Sivachenko, Lang Li
KDD
2004
ACM
173views Data Mining» more  KDD 2004»
14 years 10 months ago
A microeconomic data mining problem: customer-oriented catalog segmentation
The microeconomic framework for data mining [7] assumes that an enterprise chooses a decision maximizing the overall utility over all customers where the contribution of a custome...
Martin Ester, Rong Ge, Wen Jin, Zengjian Hu
KDD
2004
ACM
166views Data Mining» more  KDD 2004»
14 years 10 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
147views Data Mining» more  KDD 2002»
14 years 10 months ago
Sequential cost-sensitive decision making with reinforcement learning
Recently, there has been increasing interest in the issues of cost-sensitive learning and decision making in a variety of applications of data mining. A number of approaches have ...
Edwin P. D. Pednault, Naoki Abe, Bianca Zadrozny