Fraud Detection in Selection Exams Using Knowledge Engineering Tools
نویسندگان
چکیده
This paper proposes a method for fraud detection in automated selection exams, using knowledge engineering tools for identifying groups of answers with a strong indication of fraud, based on probabilistic evidence. Founded on an analysis of the wrong answers of the various candidates, the proposed method enables identification of suspicions, and evidence of fraud attempts through finding candidates with a significant number of identical wrong answers. This method of using knowledge engineering tools can be employed in various types of selection examinations, adapting to the characteristics and features of each one and contributing to the achievement of fair exams and free of fraud attempts.
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