O'Reilly logo

Building Recommendation Engines by Suresh Kumar Gorakala

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

Content-based recommender systems

In the previous section, we saw that the recommendations were generated by considering only the rating or interaction information of the products by the users, that is to say that suggesting new items for the active user is based on the ratings given to those new items by similar users to the active user.

Let's take the case of a person who has given a 4-star rating to a movie. In a collaborative filtering approach we only consider this rating information for generating recommendations. In real life, a person rates a movie based on the features or content of the movie such as its genre, actor, director, story, and screenplay. Also the person watches a movie based on their personal choices. When we are building ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required