Title

Linear Correlation Discovery in Databases: A Data Mining Approach

Publication Type

Journal Article

Publication Date

2005

Abstract

Very little research in knowledge discovery has studied how to incorporate statistical methods to automate linear correlation discovery (LCD). We present an automatic LCD methodology that adopts statistical measurement functions to discover correlations from databases’ attributes. Our methodology automatically pairs attribute groups having potential linear correlations, measures the linear correlation of each pair of attribute groups, and confirms the discovered correlation. The methodology is evaluated in two sets of experiments. The results demonstrate the methodology’s ability to facilitate linear correlation discovery for databases with a large amount of data.

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing

Research Areas

Data Management and Analytics

Publication

Data and Knowledge Engineering

Volume

53

Issue

3

First Page

311

Last Page

337

ISSN

0169-023X

Identifier

10.1016/j.datak.2004.09.002

Publisher

Elsevier

Additional URL

http://dx.doi.org/10.1016/j.datak.2004.09.002