scholar.google.com › citations
Jan 21, 2024 · This research investigates and evaluates the robustness and the resilience of the proposed Legitimacy ensemble learning model.
This research investigates and evaluates the robustness and the resilience of the proposed Legitimacy ensemble learning model. This ensemble learning model was ...
This study proposes a comprehensive framework for fake news detection integrating text, images, and videos using machine learning and deep learning techniques.
This study validates Legitimacy using a standard dataset with features relating to the credibility of news publishers to predict fake news. These features are ...
Sep 17, 2022 · This paper expands on the use of Legitimacy, a unique ensemble learning model for the task of Credibility-based Fake News Detection. This model ...
Nov 4, 2024 · Our research aims to investigate different techniques within machine learning, deep learning, and ensemble learning frameworks in Arabic fake news detection.
This paper proposes an ensemble model (EGNN) that leverages Graph Neural Networks (GNNs) and text features to enhance the accuracy of fake news detection.
Feb 1, 2024 · This study focuses on binary classification of online news articles using Artificial Intelligence, Natural Language Processing, and Machine Learning techniques.
This paper introduces RELIANCE, a pioneering ensemble learning system designed for robust information and fake news credibility evaluation. Comprising five ...
This study proposes a three-level methodology with a new model called Multi-Kernel Optimized Convolutional Neural Network (MOCNN) to investigate its ...
Missing: Examining | Show results with:Examining