From the course: Machine Learning and AI Foundations: Recommendations
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Content-based recommendations: Recommending based on product attributes
From the course: Machine Learning and AI Foundations: Recommendations
Content-based recommendations: Recommending based on product attributes
- [Instructor] Content-based recommendation systems are recommendation systems that use their knowledge of each product to recommend new products. Let's say that you tell a friend that you just watched the movie Roman Holiday starring Audrey Hepburn and that you really liked it. Your friend might recommend that you watch the movie Sabrina next. Both movies are romantic comedies and both movies feature the same movie star. It could be a good recommendation because the movies have a lot of attributes in common. This is the idea behind content-based recommendation systems. They try to recommend products that have similar attributes to a product that the user already liked. Here's an example. Let's take a look at this table of movies and how they have been rated by different users. We can see in this table that John has already given Roman Holiday a five star rating. What movie should we recommend next to John? In a content-based recommendation system, we will also have a table that gives…
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