Abstract
As mentioned in Chapter 3, our data mining algorithm, All_Gen, has been implemented in the research software tool DGG-Discover. In this chapter, we evaluate the performance of All_Gen in generating summaries from databases. We also evaluate the sixteen diversity measures for ranking the interestingness of the summaries generated, implemented in the research software tool DGGInterest. We present the results of our evaluation against a variety of metrics and describe our general experience.
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© 2001 Springer Science+Business Media New York
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Hilderman, R.J., Hamilton, H.J. (2001). Experimental Analyses. 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_6
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DOI: https://doi.org/10.1007/978-1-4757-3283-2_6
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4419-4913-4
Online ISBN: 978-1-4757-3283-2
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