6 April 2000 Data mining approach using machine-oriented modeling: finding association rules using canonical names
Author Affiliations +
Proceedings Volume 4057, Data Mining and Knowledge Discovery: Theory, Tools, and Technology II; (2000); doi: 10.1117/12.381727
Event: AeroSense 2000, 2000, Orlando, FL, United States
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.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Eric Louie, Tsau Young Lin, "Data mining approach using machine-oriented modeling: finding association rules using canonical names", Proc. SPIE 4057, Data Mining and Knowledge Discovery: Theory, Tools, and Technology II, (6 April 2000); doi: 10.1117/12.381727; https://doi.org/10.1117/12.381727
PROCEEDINGS
7 PAGES


SHARE
KEYWORDS
Data modeling

Data mining

Information operations

Silicon

Data storage

Databases

Computer science

Back to Top