3 citations · 5 across the 3 of their papers we have counts for
7 papers
Incremental Feature Learning For Infinite Data
Armin Sadreddin, Samira Sadaoui
This study addresses the actual behavior of the credit-card fraud detection environment where financial transactions containing sensitive data must not be amassed in an enormous am…
Optimizing Neural Network Weights using Nature-Inspired Algorithms
Wael Korani, Malek Mouhoub, Samira Sadaoui
This study aims to optimize Deep Feedforward Neural Networks (DFNNs) training using nature-inspired optimization algorithms, such as PSO, MTO, and its variant called MTOCL. We show…
Cost-sensitive Semi-supervised Classification for Fraud Applications
Sulaf Elshaar, Samira Sadaoui
This research explores Cost-Sensitive Learning (CSL) in the fraud detection domain to decrease the fraud class's incorrect predictions and increase its accuracy. Notably, we concen…
Effect of Word Embedding Models on Hate and Offensive Speech Detection
Safa Alsafari, Samira Sadaoui, Malek Mouhoub
Deep neural networks have been adopted successfully in hate speech detection problems. Nevertheless, the effect of the word embedding models on the neural network's performance has…
Building High-Quality Auction Fraud Dataset
Sulaf Elshaar, Samira Sadaoui
Given the magnitude of online auction transactions, it is difficult to safeguard consumers from dishonest sellers, such as shill bidders. To date, the application of Machine Learni…
Clustering and Labelling Auction Fraud Data
Ahmad Alzahrani, Samira Sadaoui
Although shill bidding is a common auction fraud, it is however very tough to detect. Due to the unavailability and lack of training data, in this study, we build a high-quality la…