AIML Journal

AIML

Issue I

ICGST

Data Warehouse based Statistical Mining

Kamal ِA. ElDahshan and Hany Maher Said Lala
Department of Mathematics, faculty of Science, Al-Azhar University, 11884, Nasr city, Cairo, Egypt

Abstract:

In this article, we employ the data warehousing technology as a preprocessing step to apply piecewise regression as a predictive data mining technique that fits a data model which will be used for prediction. Also, correlation analysis is used to qualify the best of the proposed models for that purpose. This new approach is then applied to “marketing” case of study. The conclusion of this paper is that a data warehouse accompanied with a suitable statistical data mining technique represents an effective platform for data mining.

Keywords: Data mining, data warehouse, summary tables, piecewise regression, marketing.

(P1120910670, 708 KB)

BibTex

@ARTICLE{P1120910670,

AUTHOR = {Kamal ِA. ElDahshan and Hany Maher Said Lala},

TITLE = {Data Warehouse based Statistical Mining},

JOURNAL = {ICGST International Journal on Artificial Intelligence and Machine Learning, AIML},

YEAR = {2009},

VOLUME = {9},

ISSUE ={I},

PAGES = {41--48}

}

(P1120910670, 708 KB)