Recommender Systems: Personalized Recommendations for Users

This lecture explores the challenges of content personalization for online publishers, focusing on web recommendations and personalized newsletters. It delves into the cohabitation of various algorithms, such as user-based collaborative filtering, item-based collaborative filtering, and content-based filtering. The instructor discusses the importance of data extraction, optimization of computations, and the use of approximate KNN algorithms to reduce costs and improve efficiency.