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Proceedings Paper

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

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.

Paper Details

Date Published: 6 April 2000
PDF: 7 pages
Proc. SPIE 4057, Data Mining and Knowledge Discovery: Theory, Tools, and Technology II, (6 April 2000); doi: 10.1117/12.381727
Show Author Affiliations
Eric Louie, San Jose State Univ. and IBM Almaden Research Ctr. (United States)
Tsau Young Lin, San Jose State Univ. and Univ. of California/Berkeley (United States)


Published in SPIE Proceedings Vol. 4057:
Data Mining and Knowledge Discovery: Theory, Tools, and Technology II
Belur V. Dasarathy, Editor(s)

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