Data mining approach using machine-oriented modeling: finding association rules using canonical names

Details Data mining approach using machine-oriented modeling: finding association rules using canonical names Data mining approach using machine-oriented modeling: finding association rules using canonical names

Apr 2000

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2000spie.4057..148l&link_type=abstract

Proc. SPIE Vol. 4057, p. 148-154, Data Mining and Knowledge Discovery: Theory, Tools, and Technology II, Belur V. Dasarathy; Ed.

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Scientific paper

An attribute value, in a relational model, is a meaningful label of a collection of objects; the collection is referred to as a granule of the universe of discourse. The granule itself can be regarded a label of the collection (granule); it will be referred to as the canonical name of the granule. A relational model using these canonical names themselves as attribute values (their bit patterns or lists of members) is called a machine oriented data model. For moderate size databases, finding association rules, decision rules, and etc., are reduced to easy computation of set theoretical operations of these collections. In this paper, a very fast computing algorithm is presented.

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