Authors : Dr. Mitat Uysal; M.Ozan Uysal; Dr. Aynur Uysal

Volume/Issue : Volume 10 - 2025, Issue 3 - March

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Google Scholar : https://tinyurl.com/mrxmef3p

Scribd : https://tinyurl.com/mwj2kfze

DOI : https://doi.org/10.38124/ijisrt/25mar197

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Abstract : Recommendation systems play a crucial role in various applications, including e-commerce, entertainment, and education. This paper presents a hybrid recommendation system combining AI agents with Singular Value Decomposition (SVD) and Non-negative Matrix Factorization (NMF) to improve accuracy and efficiency. We evaluate the performance of this approach through a Python implementation, ensuring that the system does not rely on external libraries such as Scikit-Learn. The results are visualized using graphical representations for better interpretability. The proposed model is validated against benchmark datasets, and the experimental results demonstrate its effectiveness in providing accurate recommendations.

Keywords : SVD,NMF,Hybrid Recommendation System,AI Agent,Optimization.

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