Applications of Transformers in Recommendation Models: Capturing Long-Term DependenciesOptimization Strategies
Abstract
Transformer architecture has transformed this aspect of recommendation systems by dismantling theunderlying constraints of long-term dependencies and intricate behavioural patterns. The self-attentionmechanism permits dynamic weighting of past interactions according to contextual similarity instead of temporal closeness in order to permit
Fields of Study & Subjects
Recommender Systems and Techniques
Information Retrieval and Search Behavior
Topic Modeling
Publication details
- Journal / source
- Journal of Computational Analysis and Applications
- Publication date
- 5 January 2026