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

• Autorzy: Rauch J.

Identyfikatory

DOI

10.3233/FI-2016-1420

• Konferencja: Rough Set Theory Workshop (RST’2015); (6; 29-06-2015; University of Warsaw )
• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

data mining; association rules; formalization of CRISP-DM; domain knowledge; logical calculus of association rules

• Wydawca: IOS Press
• Czasopismo: Fundamenta Informaticae
• Rocznik: 2016
• Tom: Vol. 148, nr 1/2
• Strony: 1--33
• Opis fizyczny: Bibliogr. 32 poz., tab.

Twórcy

autor

Rauch J.

• University of Economics, Prague, nám. W. Churchilla 4, 130 67 Prague 3, Czech Republic

Bibliografia

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Uwagi

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).