Classification in Business Intelligence using Variable Consistency Dominance-based Rough Set Approach
• 2013
معلومات البحث
المؤلفون
S.m ABOELNAGA, h.m abdelkader
الكلمات المفتاحية
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المجلة العلمية
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الناشر
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المجلد
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العدد
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الصفحات
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publication.type
Local
رابط البحث
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المواد المرفقة
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الملخص
— 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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