Knowledge discovery in databases: the purpose, necessity, and challenges

Authors:
Willi Klösgen;Jan M. Zytkow
Affiliations:
Principal Researcher, Fraunhofer Institute for Autonomous Intelligent Systems, Sankt Augustin, Germany;Professor of Computer Science, University of North Carolina at Charlotte
Venue:
Handbook of data mining and knowledge discovery
Year:
2002

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Abstract

This section introduces knowledge discovery in databases (KDD) as a field that is driven by the need for knowledge derived from massive and varied data. We explain both the necessary role of KDD and the conditions under which KDD methods can be profitably applied. Together, application needs and successful methods stimulated the fast development of KDD into a field that is established both in academia and industry. To understand the results and challenges of knowledge discovery we categorize knowledge resulting from KDD along several dimensions. Then we outline many challenges crucial to the further growth of KDD.