Technology
How does a recommendation algorithm work?
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.
See it in motion.
Watch a 2-minute animated lesson that shows exactly how a recommendation algorithm works.
Step by step
- 1It tracks what you click, watch, buy, or rate.
- 2It finds people with similar tastes and items similar to ones you liked.
- 3It predicts how much you'd like things you haven't seen yet.
- 4It ranks and shows you the top predictions.
- 5It powers feeds on streaming, shopping, and social apps.
Frequently asked questions
- 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.