Recommender Systems Complete Course Beginner to Advanced - Basics of Recommender System: Content-Based Filtering

The video tutorial discusses content-based filtering in recommendation systems, explaining how it predicts user preferences based on item features and user interactions. It highlights the advantages, such as not needing data from other users and being effective in niche tasks, and the disadvantages, including the need for domain knowledge and limitations with new users. The tutorial concludes by transitioning to collaborative filtering.

How does user behavior affect the performance of a content based recommendation system?

In what scenarios is content based filtering particularly useful?