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Béatrice Duval and Ansaf Salleb and Christel Vrain
On the Discovery of Exception Rules: A Survey
, Chapitre Quality Measures in Data Mining
, Chapitre in Quality Measures in Data Mining Book
, Springer in the Series Studies in Computational Intelligence
, 2006
, \aparaitre
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Abstract
In this paper, we present a survey of the different approaches developed for
mining exception rules. Exception rules are interesting in the context of
quality measures since such rules are intrinsically satisfied by few
individuals in the database and many criteria relying on the number of
occurrences, such as for instance the support measure, are no longer relevant.
Therefore traditional measures must be coupled with other criteria. In that
context, some works have proposed to use the expert's knowledge: she/he can
provide the system either with constraints on the syntactic form of the rules,
thus reducing the search space, or with commonsense rules that have to be
refined by the data mining process. Works that rely on either of these
approaches, with their particular quality evaluation are presented in this
survey. Moreover, this presentation also gives ideas on how numeric criteria
can be intertwined with user-centered approaches.
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