- Bilgisayar Bilimleri
- Cilt: 10 Sayı: 1
- Current Trends in Recommender Systems: A Survey of Approaches and Future Directions
Current Trends in Recommender Systems: A Survey of Approaches and Future Directions
Authors : Berke Akkaya
Pages : 53-91
Doi:10.53070/bbd.1652022
View : 63 | Download : 67
Publication Date : 2025-06-01
Article Type : Research Paper
Abstract :This paper discusses the growing importance of recommender systems in enhancing user experience and information access in digital environments. It identifies challenges such as data sparsity, the cold-start problem, and scalability, emphasizing the need for advanced machine learning techniques. Various methodologies are explored, including collaborative filtering, content-based filtering, and hybrid approaches. Innovations like graph-based collaborative filtering, graph neural networks, and deep learning are highlighted for addressing data sparsity and complex data relationships. The paper also emphasizes attention mechanisms and sequential modeling to resolve the cold-start problem and adapt to changing user preferences. It stresses the significance of explainable AI for building user trust and transparency. Looking ahead, the paper anticipates advancements in cross-domain recommendation models and the integration of diverse data sources to enhance personalization and relevance. Overall, it advocates for sophisticated methodologies to overcome challenges and improve user satisfaction in digital platforms, underscoring the role of innovation in the future of recommendation technologiesKeywords : Öneri Sistemleri, İşbirlikçi Filtreleme, İçerik Tabanlı Filtreleme, Hibrit Öneri Yaklaşımları
ORIGINAL ARTICLE URL