MovieLens

Researchers introduced a multi-objective reinforcement learning framework for recommender systems that uses a Pareto-DQN agent with semantic embeddings to optimize engagement, diversity, and fairness …

A team of engineers building recommendation systems for financial services clients found that collaborative filtering fails structurally in fintech due to sparse interaction data, cold-start problems,…

A developer built CineMatch AI, a movie recommendation system using item-based collaborative filtering on the MovieLens dataset. The system compares movies using cosine similarity based on historical …