Recommender Systems with Machine Learning - Taxonomy of Recommender Systems

The video tutorial covers the taxonomy of recommender systems, dividing them into personalized and non-personalized categories. It delves into content-based filtering, which recommends items similar to those users liked before, and collaborative filtering, which relies on user opinions. The tutorial also introduces context-aware and hybrid systems, which use multiple information sources to enhance recommendations.

What are context-aware recommender systems and how do they improve recommendations?

Explain the concept of hybrid recommender systems.

What role do side information and new techniques play in developing hybrid algorithms?