Development of Efficient Data Mining Techniques for Fraud Identification

Alowais, Mohammed Ibrahim (2012) Development of Efficient Data Mining Techniques for Fraud Identification. Masters thesis, Multimedia University.

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Abstract

This study examine the credit card fraud problem and adopt some actual transactional data with an online questionnaire transaction data to identify and prevent fraud. The ultimate aim of this study is to compare the effectiveness of generating personalized classification model to represent the spending behavior of individuals in identifying fraud as compared to the general classification model constructed from the mass data collected from all individuals.

Item Type: Thesis (Masters)
Subjects: H Social Sciences > HV Social pathology. Social and public welfare
Depositing User: Users 1102 not found.
Date Deposited: 03 Dec 2012 01:26
Last Modified: 03 Dec 2012 01:26
URI: http://shdl.mmu.edu.my/id/eprint/3652

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