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How does a recommendation algorithm work?
Quick answer
A recommendation algorithm works by learning your tastes from your behavior and suggesting things you're likely to enjoy. It compares what you've watched, bought, or liked with patterns from millions of others to predict what you'll want next. It tracks what you click, watch, buy, or rate.
Step by step
- It tracks what you click, watch, buy, or rate.
- It finds people with similar tastes and items similar to ones you liked.
- It predicts how much you'd like things you haven't seen yet.
- It ranks and shows you the top predictions.
- It powers feeds on streaming, shopping, and social apps.
People also ask
How does a recommendation system know what I like?
It learns from your activity and compares it with patterns from many other users to predict items you're likely to enjoy.
What is collaborative filtering?
A common method that recommends things liked by people whose tastes resemble yours — 'people like you also liked this.'
Why do recommendations sometimes feel repetitive?
They lean on what you already engage with, so they can create a 'bubble'; many systems deliberately add variety to counter it.
How does YouTube or Netflix recommend things?
By learning your behavior and matching it to patterns from similar users and similar content, then ranking suggestions.
Why do recommendations sometimes feel too accurate?
They draw on huge amounts of behavioral data and find subtle patterns you may not notice yourself.
Part of the guide: How AI Works →