An intelligent middleware for linear correlation discovery

Cecil Eng Huang Chua

doi:10.1016/S0167-9236(01)00127-0

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An intelligent middleware for linear correlation discovery

2002-03-01

Cecil Eng Huang Chua

Roger H.L. Chiang *

Ee‐Peng Lim

DOI：10.1016/S0167-9236(01)00127-0

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Abstract

En 中文

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. 2002 Elsevier Science B.V. All rights reserved.

Keywords:

software integration

middleware

data mining

knowledge discovery

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