5 papers
Contextual Attention-Based Multimodal Fusion of LLM and CNN for Sentiment Analysis
Meriem Zerkouk, Miloud Mihoubi, Belkacem Chikhaoui
This paper introduces a novel approach for multimodal sentiment analysis on social media, particularly in the context of natural disasters, where understanding public sentiment is…
A Comprehensive Review of AI-based Intelligent Tutoring Systems: Applications and Challenges
Meriem Zerkouk, Miloud Mihoubi, Belkacem Chikhaoui
AI-based Intelligent Tutoring Systems (ITS) have significant potential to transform teaching and learning. As efforts continue to design, develop, and integrate ITS into educationa…
SentiDrop: A Multi Modal Machine Learning model for Predicting Dropout in Distance Learning
Meriem Zerkouk, Miloud Mihoubi, Belkacem Chikhaoui
School dropout is a serious problem in distance learning, where early detection is crucial for effective intervention and student perseverance. Predicting student dropout using ava…
Beyond classical and contemporary models: a transformative AI framework for student dropout prediction in distance learning using RAG, Prompt engineering, and Cross-modal fusion
Miloud Mihoubi, Meriem Zerkouk, Belkacem Chikhaoui
Student dropout in distance learning remains a critical challenge, with profound societal and economic consequences. While classical machine learning models leverage structured soc…
Dynamic Sparse Causal-Attention Temporal Networks for Interpretable Causality Discovery in Multivariate Time Series
Meriem Zerkouk, Miloud Mihoubi, Belkacem Chikhaoui
Understanding causal relationships in multivariate time series (MTS) is essential for effective decision-making in fields such as finance and marketing, where complex dependencies…