From the course: Building a Recommendation System with Python Machine Learning and AI

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Popularity-based recommenders

Popularity-based recommenders

From the course: Building a Recommendation System with Python Machine Learning and AI

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Popularity-based recommenders

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- [Instructor] 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 account of the number of ratings that were given to each 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 one is preferable to users over place two. You can see the logic more clearly here. Based on the number of users or guests that rated place one and place two, we'd say that place one is more popular than place two, and so based on popularity, place one would be recommended over place two. Let's look at the types of data that popularity recommenders use. Popularity-based recommenders rely on purchase history. They're often…

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