What is the long-tail problem in recommendation systems?

Jun 29, 2023 ... A recommender system uses artificial intelligence (AI), machine learning, and big data to suggest items a user might be interested in. This system uses different sensors for extracting data continuously regarding temperature, PH and Turbidity etc. These parameters can be analysed in real-time ... Dec 20, 2023 ... Design a video recommendation system that presents recommendations on a homepage like YouTube to increase engagement. 3 days ago ... Gained familiarity with various machine learning algorithms used in recommendation systems, such as matrix factorization and deep learning ... Feb 13, 2023 ... The proposed collaborative filtering (CF) method categorizes active learners into one learner group. The proposed model has experimented on ... Apr 19, 2021 ... I developed a game recommendation system model. It was an extremely complex development for me, as I am still gaining experience and knowledge in Machine ... ApplyingML · Reinforcement Learning for Recommendation Systems · Contextual bandits: Multi-armed bandits with context · Value-based: Learning value for each ... Apr 21, 2024 ... What's the current state of recommendation algorithms/systems in machine learning research? [D] ... When I first started my ML journey about 4 ... Apr 22, 2025 ... Recommendation engines in this category rely on machine learning algorithms, such as clustering models, regression, user-based k-nearest ... The proposed livestreaming e-commerce recommendation system (LERS) enhances the exploration of new items by incorporating uncertainty into neural networks.