From the course: Building a Recommendation System with Python Machine Learning & AI
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Popularity-based recommenders - Python Tutorial
From the course: Building a Recommendation System with Python Machine Learning & AI
Popularity-based recommenders
- [Narrator] Turning now to popularity-based recommendation systems. Popularity-based recommenders offer a very primitive form of collaborative filtering, where items are recommended to users based on how popular those items are among other users. So in the drawing here, Place represents item we are recommending, and we are going to take a count of the number of ratings that were given to eat Place. The assumption is that the places that have the most number of ratings or reviews are the most popular. Hence, we make the popularity-based recommendation that Place 1 is preferable to users over Place 2. You can see the logic more clearly here. Based on the number of users or guests that rated Place 1 and Place 2, we'd say that Place 1 is more popular than Place 2. So, based on popularity, Place 1 would be recommended over Place 2. Let's look at the types of data that popularity recommenders use. Popularity-based recommenders rely on purchase history. They're often used by news sites…
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