Predictive data mining: new techniques and applications.

In this age of computerized data processing, more and more structured data becomes available. This is mainly driven by the automation of processes, and innovative storage technologies. Although useful and valuable knowledge is hidden in these vast amounts of data, it is typically hidden. Data mining entails the automatic inferring of patterns and knowledge from this data in order to come to a better decision making process. The need for proper, intelligent and usable decision support systems, that include such mined knowledge, is greater than ever. The theoretical part of the research will focus on methods that can improve data quality, and by developing new predictive data mining algorithms that are tailored to the business needs. The newly developed algorithms will then be validated in several practical, real-life problem settings.

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Disciplines:Applied mathematics in specific fields, Computer architecture and networks, Distributed computing, Information sciences, Information systems, Programming languages, Scientific computing, Theoretical computer science, Visual computing, Other information and computing sciences, Applied economics