A Hybrid Recommendation System Using AI Agent, Singular Value Decomposition (SVD), and Non-negative Matrix Factorization (NMF)
Year: 2025
Type: article
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.
Authors: Mitat Uysal, M.Ozan Uysal, Aynur Uysal
Institution: Doğuş University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4408628314