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AI-driven personalisation represents a transformative innovation in mobile application development, revolutionising user engagement across domains such as e-commerce, social media, education and healthcare. By leveraging cutting-edge machine learning (ML) and deep learning frameworks, these systems deliver real-time, context-aware and user-specific recommendations, significantly enhancing user interaction, retention and satisfaction. This study provides a systematic review of foundational methodologies, including collaborative filtering, deep neural networks and transformer-based architectures, examining their application across diverse industries. A particular focus is placed on multimodal and context-aware approaches that underpin adaptive, scalable and privacy-conscious solutions.
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Nwanna et al. (2025) studied this question.
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