A Conceptual Framework of Data Mining - Data Mining: Foundations and Practice - page 499

explained, in order to result an explanatory account one needs to do the foll-
owing: First, propose the heuristic for some explanation profiles, transform
and associate them with the environment where the target pattern is located.
Then, construct some rules by a particular method in the explanation con-
text. After these, the learned results need to be evaluated. According to the
evaluation results and the user feedback, the explanation profiles can be sharp-
ened and refined, the same or different methods can be applied to the refined
context for another plausible explanation construction until it is satisfied.
5 Conclusion
A three-layered conceptual framework of data mining is discussed in this
chapter, consisting of the philosophy layer, the technique layer and the appli-
cation layer. The philosophy layer deals with the formation, representation,
evaluation, classification and organization, and explanation of knowledge; the
technique layer deals with the technique development and innovation; and
the application layer emphasizes on the application, utility and explanation
of mined knowledge. The layered framework focuses on the data mining ques-
tions and issues in different abstract levels, and thus, offers us opportunities
and challenges to reconsider the existing three views of data mining. The
framework is aimed at the understanding of the data mining as a field of
study, rather than a collection of theories, algorithms and tools.
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