Abstract
The data mining step in KDD specifies the task to be performed, such as summarization or anomaly-detection. In this chapter, we introduce the data structures and algorithms utilized by our data mining technique. These data structures and algorithms have been incorporated into DGG-Discover and DGG-Interest, extensions to DB-Discover, a research software tool for KDD developed at the University of Regina [22, 23, 24, 25, 50, 65, 66, 70, 72].
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© 2001 Springer Science+Business Media New York
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Hilderman, R.J., Hamilton, H.J. (2001). A Data Mining Technique. In: Knowledge Discovery and Measures of Interest. The Springer International Series in Engineering and Computer Science, vol 638. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-3283-2_3
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DOI: https://doi.org/10.1007/978-1-4757-3283-2_3
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4419-4913-4
Online ISBN: 978-1-4757-3283-2
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