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Time-Aware CF and Temporal Association Rule-Based Personalized Hybrid Recommender System
2021
Journal of Organizational and End User Computing
Most recommender systems usually combine several recommendation methods to enhance the recommendation accuracy. Collaborative filtering (CF) is a best-known personalized recommendation technique. While temporal association rule-based recommendation algorithm can discover users' latent interests with time-specific leveraging historical behavior data without domain knowledge. The concept-drifting and user interest-drifting are two key problems affecting the recommendation performance. Aiming at
doi:10.4018/joeuc.20210501.oa2
fatcat:griyrls44bh4tfnoosvemekg3q