Publication Type
Journal Article
Version
publishedVersion
Publication Date
3-2002
Abstract
Although it is widely accepted that research from data mining, knowledge discovery, and data warehousing should be synthesized, little research addresses the integration of existing data management and analysis software. We develop an intelligent middleware that facilitates linear correlation discovery, the discovery of associations between attributes and attribute groups. This middleware integrates data management and data analysis tools to improve traditional data analysis in three perspectives: (1) identify appropriate linear correlation functions to perform based on the semantics of a data set; (2) execute appropriate functions contained in the data analysis packages; and (3) derive useful knowledge from data analysis.
Discipline
Databases and Information Systems | Numerical Analysis and Scientific Computing
Publication
Decision Support Systems
Volume
32
Issue
4
First Page
313
Last Page
326
ISSN
0167-9236
Identifier
10.1016/S0167-9236(01)00127-0
Publisher
Elsevier
Citation
CHUA, Cecil; CHIANG, Roger Hsiang-Li; and LIM, Ee Peng.
An intelligent middleware for linear correlation discovery. (2002). Decision Support Systems. 32, (4), 313-326.
Available at: https://ink.library.smu.edu.sg/sis_research/57
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://doi.org/10.1016/S0167-9236(01)00127-0
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons