From the course: Building Recommender Systems with Machine Learning and AI

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Item-based collaborative filtering

Item-based collaborative filtering - Python Tutorial

From the course: Building Recommender Systems with Machine Learning and AI

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Item-based collaborative filtering

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- Another way to do collaborative filtering is by flipping the problem on its head. Instead of looking for other people similar to you, and recommending stuff they liked, look at the things you liked, and recommend stuff that's similar to those things. We call this item-based collaborative filtering, instead of user-based. There are a few reasons why using similarities between items could be better than similarities between people. One is that items tend to be of a more permanent nature than people, a math book will always be a math book, but an individual's tastes may change very quickly over the span of their lives. So focusing on the similarities between unchanging objects can produce better results than looking at similarities between people, who may have liked something last week, and something totally different this week. Your math book will always be similar to other math books, but a person who liked a math book might be bored with math a few months from now. As such, you can…

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