Problem Framing, Metrics, and Scale
~40 min read
How to scope a recommendation system: defining the problem, choosing the right success metric, establishing scale assumptions, and identifying the core challenges before touching any model design.
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Key points
- •The context (homepage vs. post-watch vs. search) changes the design — always clarify before designing
- •Choosing the right success metric is the highest-leverage design decision: watch time > CTR for video recommendation, but watch time alone can reward addictive content
- •Cold start (new users, new videos) and the filter bubble are first-class problems, not afterthoughts — name them in the framing phase