This document proposes a new approach to movie recommendation that considers temporal dynamics and local user ratings. The current best approach is collaborative filtering with temporal dynamics, but this new approach clusters users based on their individual monitoring and behavior over time. It also clusters movies based on their global and dynamic class ratings. The model would monitor users, user-user patterns, user-movie patterns, and movie-movie patterns over time to update recommendations and predictions. This is aimed to provide more accurate recommendations by considering how user preferences can change over time.