Integrating Transformers into Recommendation Systems: A Hybrid Approach

Author(s)	Mitat Uysal, Aynur Uysal, M.Ozan Uysal
Country	Turkey
Abstract	In recent years, recommendation systems have become essential for various industries, from e-commerce to social media. This paper explores the integration of Transformer models within recommendation systems, which enhances the model's ability to capture long-range dependencies in user interactions. We present a hybrid recommendation approach combining collaborative filtering and Transformer-based content analysis. A case study is included, demonstrating how this integration handles both cold-start problems and typical user-item recommendation tasks.
Keywords	Recommendation systems, Transformers, Hybrid recommendation, Cold-start,Collaborative filtering
Field	Engineering
Published In	Volume 6, Issue 6, November-December 2024
Published On	2024-11-27
Cite This	Integrating Transformers into Recommendation Systems: A Hybrid Approach - Mitat Uysal, Aynur Uysal, M.Ozan Uysal - IJFMR Volume 6, Issue 6, November-December 2024. DOI 10.36948/ijfmr.2024.v06i06.30633
DOI	https://doi.org/10.36948/ijfmr.2024.v06i06.30633
Short DOI	https://doi.org/g8r8k2

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International Journal For Multidisciplinary Research