Data Mining-based Fraud Detection Research: A Comprehensive Survey

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A Comprehensive Survey of Data Mining-based Fraud
Detection Research
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outline
• Introduction
• Technical reviews of different research paper
• Targeted sections
• Types of fraudsters
• Data and measurement
• Performance measures
• Methods and technique
• Supervised Approach on the labeled
• Critique of Methods and techniques
• Conclusion
• Resources

Introduction
• Analysis of paper
• Importance of data mining
• How data mining resolve the issues
related fraud detection system?

Technical reviews of different research paper
• Targeted sections
• Types of fraudsters
• Data and its measurement
• Performance measures

Technical reviews of different research paper
• What kind of software use in fraud
detection system?
• What is the objective of fraud
detection system?

Targeted sections
• What kind of societies are targeted in
this research paper?
• How data mining help to reduce the
risk of fraud detection?

Types of fraudsters
• How many types of fraudsters?
• How these fraudsters involved in
criminal activities?
• How data mining help to enhance the
fraud detection system?

Data and measurement
• Describe the numerical values of data
and its attributes?
• How these set of image help to
analyze this data?

Performance measures
• How fraud departments predict
values ?
• How many errors in thi performance
measures ?

Methods and technique

Supervised Approach on the labeled
• How fuzzy neural networks speed up
the process for the detection of fraud
system?
• Give the different reviews of research
paper?

Conclusion
• what are things which are explained
in the research paper ?
• How this research paper will help to
remove the fraud detection system?