<ul><li>Recommender systems (RS) are essential for generating personalized suggestions based on user preferences, historical interactions, and item attributes.</li><li>Research on RS has increasingly incorporated advanced deep learning (DL) techniques to overcome traditional limitations.</li><li>Researchers from Mansoura University have introduced the HRS-IU-DL model, an advanced hybrid recommendation system that integrates multiple techniques to enhance accuracy and relevance.</li><li>The proposed hybrid model (HRS-IU-DL) was evaluated on the Movielens 100k dataset, achieving superior performance across metrics and outperforming baseline models.</li></ul>

Hybrid Recommendation System (HRS-IU-DL): Enhancing Accuracy and Personalization with Deep Learning Techniques

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