Joint mining of multiple data sets can often discover interesting, novel, and reliable patterns which cannot be obtained solely from any single source. For example, in cross-marke...
Data mining techniques frequently find a large number of patterns or rules, which make it very difficult for a human analyst to interpret the results and to find the truly interes...
Kaidi Zhao, Bing Liu, Thomas M. Tirpak, Weimin Xia...
This paper describes our experience with applying data mining techniques to the problem of fraud detection in spatio-temporal health data in Medicare Australia. A modular framework...
Kee Siong Ng, Yin Shan, D. Wayne Murray, Alison Su...
Abstract. We study the problem of predictive data mining in the competitive multi-agent setting, in which each agent is assumed to have some partial knowledge needed for correctly ...
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...