DGGs, a data structure for describing and guiding the generation of summaries from databases, were introduced.
Serial and parallel algorithms for traversing the generalization space described by DGGs were introduced and evaluated.
The use of diversity measures as measures of interestingness for summaries generated from databases was introduced and evaluated.
A preliminary foundation for a theory of interestingness within the context of ranking the interestingness of summaries generated from databases was developed.
KeywordsDiversity Measure Data Mining Technique Unknown Distribution Interestingness Measure Discovery Task
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