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Addressing data sparsity and cold-start challenges in recommender systems using advanced deep learning and self-supervised learning techniques.

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Title: Addressing data sparsity and cold-start challenges in recommender systems using advanced deep learning and self-supervised learning techniques.
Authors: Karabila, Ikram1, ikram.karabila@usmba.ac.ma, Darraz, Nossayba1, El-Ansari, Anas2, Alami, Nabil3, El Mallahi, Mostafa1
Source: Journal of Experimental & Theoretical Artificial Intelligence; Nov2025, Vol. 37 Issue 8, p1421-1451, 31p
Database: Applied Science & Technology Source
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DbLabel: Applied Science & Technology Source
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PubType: Academic Journal
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  Data: Addressing data sparsity and cold-start challenges in recommender systems using advanced deep learning and self-supervised learning techniques.
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Experimental+%26+Theoretical+Artificial+Intelligence%22">Journal of Experimental & Theoretical Artificial Intelligence</searchLink>; Nov2025, Vol. 37 Issue 8, p1421-1451, 31p
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        Value: 10.1080/0952813X.2024.2401364
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        Text: English
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        PageCount: 31
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              M: 11
              Text: Nov2025
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              Y: 2025
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