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Logical Aspects of Dealing with Domain Knowledge in Data Mining with Association Rules

Rauch J.

Fundamenta Informaticae

2016

Vol. 148, nr 1/2

1--33

Association rules are introduced as general relations of two general Boolean attributes derived from columns of an analysed data matrix. Expressive power of such association rules makes possible to use various items of domain knowledge in data mining. Each particular item of domain knowledge is mapped to a set of simple association rules. Simple association rules together with their logical consequences are understood as a set of consequences of a given item of domain knowledge. Such sets of consequences are used when interpreting results of a data mining procedure. Logical deduction plays a crucial role in this approach. New results on related deduction rules are presented.

Formal Framework for Data Mining with Association Rules and Domain Knowledge : Overview of an Approach

Rauch J.

Fundamenta Informaticae

2015

Vol. 137, nr 2

171--217

A formal framework for data mining with association rules is introduced. The framework is based on a logical calculus of association rules which is enhanced by several formal tools. The enhancement allows the description of the whole data mining process, including formulation of analytical questions, application of an analytical procedure and interpretation of its results. The role of formalized domain knowledge is discussed.