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* you could include the product that's maximally different, the second most similar, you could exclude products within the same category, you could choose rando
by Pamar 7y ago
* you could include the product that's maximally different, the second most similar, you could exclude products within the same category, you could choose randomly and weight by conversion rate*
This is interesting. Has anyone tried that or knows of a website that uses this?
- xpe 7y agoThe exploration versus exploitation tradeoff is well studied in bandit algorithms and reinforcement learning in general.
- jrumbut 7y agoI have personally implemented discarding the top-n (small n, like 3-5) most similar results in a recommendation system as well as adding a totally random item in the results but it was a small scale system. The top-n removal was a small but noticeable amount better. That was in part due to the specific content in the database as well as the audience, but it's a thing to try I believe.