Enhancing sparse data recommendations with self-inspected adaptive SMOTE and hybrid neural networks

Enhancing sparse data recommendations with self-inspected adaptive SMOTE and hybrid neural networks

Abstract Personalized recommendation systems are vital for enhancing user satisfaction and reducing information overload, especially in data-sparse environments like e-commerce platforms. This paper introduces a novel hybrid framework that combines Long Short-Term Memory (LSTM) with a modified Split...

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Main Authors: Ramesh Vatambeti, Hari Prasad Gandikota, D. Siri, G. Satyanarayana, Narasimhula Balayesu, M. Ganesh Karthik, Koteswararao Ch
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Personalized recommendation systems
Long short-term memory
Quokka swarm optimization
Hybrid mutation based white shark optimizer
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Online Access:https://doi.org/10.1038/s41598-025-02593-9
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https://doi.org/10.1038/s41598-025-02593-9

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