Current knowledge discovery systems are armed with many data mining techniques that can be potentially applied to a new problem. However, a system faces a challenge of selecting t...
Mykola Pechenizkiy, Alexey Tsymbal, Seppo Puuronen
Predictive data mining typically relies on labeled data without exploiting a much larger amount of available unlabeled data. The goal of this paper is to show that using unlabeled...
Kang Peng, Slobodan Vucetic, Bo Han, Hongbo Xie, Z...
We show that the e-commerce domain can provide all the right ingredients for successful data mining. We describe an integrated architecture for supporting this integration. The ar...
Suhail Ansari, Ron Kohavi, Llew Mason, Zijian Zhen...
Most knowledge discovery processes are biased since some part of the knowledge structure must be given before extraction. We propose a framework that avoids this bias by supporting...
Over the past 15 years, numerous algorithms have been proposed for frequent pattern mining as it plays an essential role in many knowledge discovery and data mining (KDD) tasks. M...