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Ass. Lect. Somia Mohamed Mahmoud Abou Elnaga :: Publications:

Title:
Classification in Business Intelligence using Variable Consistency Dominance-based Rough Set Approach
Authors: S.m ABOELNAGA, h.m abdelkader
Year: 2013
Keywords: Not Available
Journal: Not Available
Volume: Not Available
Issue: Not Available
Pages: Not Available
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Local/International: Local
Paper Link: Not Available
Full paper Not Available
Supplementary materials Not Available
Abstract:

— Business Intelligence (BI) is the ability for an organization to take all its capabilities and convert them into knowledge. Common functions of business intelligence technologies are reporting, online analytical processing, analytics, data mining, process mining, business performance management, benchmarking, text mining, predictive analytics and prescriptive analytics. Financial systems such as private banking system are considered as a sector of BI. In this study, we use the Variable Consistency Dominance-based Rough Set Approach (VC-DRSA) as a classification method to extract a set of rules that provide recommendations of behaviors that increase the risk in financial processes. A set of rules is derived from a data set of banking system and its predictive ability is evaluated. Then, we show how the generated rules deal with new customers. The effectiveness of VC-DRSA is shown by the result of C4.5 method as another classification method.

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