Results 81 to 90 of about 34,999 (183)
An Experimental Study With Imbalanced Classification Approaches for Credit Card Fraud Detection
IEEE Access, 2019 Credit card fraud is a criminal offense. It causes severe damage to financial institutions and individuals. Therefore, the detection and prevention of fraudulent activities are critically important to financial institutions.
Sara Makki +5 more
doaj +1 more source
Analyses of Social Issues and Public Policy, Volume 26, Issue 2, August 2026.Abstract This mixed‐methods study examines the experience of the impostor phenomenon in a racially/ethnically and sexually diverse sample of undergraduates in majors related to science, technology, engineering, and math (STEM). Guided by an intersectionality framework, we examined whether experiences of the impostor phenomenon differ at the ...
Richard Chang +3 more
wiley +1 more source
Радіоелектронні і комп'ютерні системиThe subject matter of this article is enhancing credit card fraud detection systems by exploring the impact of oversampling rates and ensemble methods with diverse feature selection techniques.
Mohamed Akouhar +3 more
doaj +1 more source
Adaptive Model for Credit Card Fraud Detection
International Journal of Interactive Mobile Technologies (iJIM), 2020 <p>While the flow of banking transactions is increasing, the risk of credit card fraud is becoming greater particularly with the technological revolution that we know, fraudulent are improve and always find new methods to deal with the preventive measures that financial systems set up.
Imane Sadgali +2 more
openaire +3 more sources
On Using the Shapley Value for Anomaly Localization: A Statistical Investigation
Applied AI Letters, Volume 7, Issue 2, June 2026.ABSTRACT Recent publications have suggested using the Shapley value for anomaly localization for sensor data systems. We use a reasonable statistical model for the classifiers required to compute the Shapley value to provide repeatable and rigorous analysis in the anomaly localization application.
Rick S. Blum +2 more
wiley +1 more source
Quantum Autoencoder for Enhanced Fraud Detection in Imbalanced Credit Card Dataset
IEEE AccessCredit card fraud detection is crucial for financial security which entails identifying unauthorized transactions that can result in significant financial losses.
Chansreynich Huot +3 more
doaj +1 more source
Tuned Out or Dialed In: How Attributions Shape Observer Reactions to Music Listeners at Work
Personnel Psychology, Volume 79, Issue 2, Page 223-250, Summer 2026.ABSTRACT Music listening while working is prevalent in contemporary workplaces, with extensive research demonstrating its psychological and behavioral implications. Shifting focus from intra‐individual outcomes, the present research examines the social implications of music listening at work.
Oguz Gencay +2 more
wiley +1 more source
Expert Systems, Volume 43, Issue 5, May 2026.ABSTRACT Credit card fraud detection remains a challenging research problem due to the class imbalance issue caused by the rarity of fraudulent transactions. Classical oversampling techniques such as SMOTE, ADASYN and their variants help balance data but do not reflect the nonlinear structure of real‐world fraud, leading to poor generalization.
Sultan Alharbi +2 more
wiley +1 more source
A Hybrid Deep Learning Approach with Generative Adversarial Network for Credit Card Fraud Detection
TechnologiesCredit card fraud detection is a critical challenge in the financial industry, with substantial economic implications. Conventional machine learning (ML) techniques often fail to adapt to evolving fraud patterns and underperform with imbalanced datasets.
Ibomoiye Domor Mienye, Theo G. Swart
doaj +1 more source
Feature Selection in Large Scale Data Stream for Credit Card Fraud Detection [PDF]
, 2009 There is increased interest in accurate model acquisition from large scale data streams. In this paper, because we have focused attention on time-oriented variation, we propose a method contracting time-series data for data stream.
Ise, Masayuki +2 more
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