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My instinct is that they are willing to live with showing some comparatively weak recommendations occasionally if that means not adding layers and layers of exc

My instinct is that they are willing to live with showing some comparatively weak recommendations occasionally if that means not adding layers and layers of exceptions on top of their basic recommendation engine. And/or they have projected that the ROI isn't there for building in more sophisticated recommendations.

resu_nimda 9y ago
At Amazon's scale, a very very small increase in the effectiveness of recommendations can represent millions in revenue. They probably do have layers of exceptions, and custom-built software used by teams of "editors" to manually manage these exceptions. Not to mention the experimentation system where they are simultaneously testing hundreds of things from CSS one-liners to new ranking algorithms. It's probably a pretty complex beast with the weight and inertia of a core system that's been continuously in production through 20 years of growth. They probably continue to invest heavily in it, the ROI is there, it's just a really hard problem for them at this point. Their engineers probably curse its limitations and would love to rewrite/replace old and outdated parts, and indeed there will be teams working on that, but those projects will either die out or spend so much time reaching feature parity with the bloated existing system that it ends up looking much the same.
baddox 9y ago
Why would this be an "exception"? The basic item-based collaborative filtering described at the beginning of the article finds items that are likely to be purchased by someone who has purchased a specific item. I'm pretty sure that it's true that someone who buys a vacuum is much more likely to buy another vacuum. It may seem counterintuitive, and may not be true for you after you just bought a vacuum, but I see no reason to believe that Amazon's algorithm isn't working properly and giving Amazon a lot of value.
- blacksmith_tb 9y ago
  It seems like we're all saying the same things - I agree it is likely that someone who has bought a vacuum before is more likely to buy another. But to make the recommendations really shine, it should wait n months before suggesting that again, where n will vary quite a lot by product type - those are the sort of exceptions I'm talking about.
freyr 9y ago
It should not require layers and layers of exceptions to categorize products that get repeat buys (paper towels), similar buys (detective novels), or one-time buys (vacuum cleaners), and make recommendations accordingly.

resu_nimda 9y ago

At Amazon's scale, a very very small increase in the effectiveness of recommendations can represent millions in revenue. They probably do have layers of exceptions, and custom-built software used by teams of "editors" to manually manage these exceptions. Not to mention the experimentation system where they are simultaneously testing hundreds of things from CSS one-liners to new ranking algorithms. It's probably a pretty complex beast with the weight and inertia of a core system that's been continuously in production through 20 years of growth. They probably continue to invest heavily in it, the ROI is there, it's just a really hard problem for them at this point. Their engineers probably curse its limitations and would love to rewrite/replace old and outdated parts, and indeed there will be teams working on that, but those projects will either die out or spend so much time reaching feature parity with the bloated existing system that it ends up looking much the same.

baddox 9y ago

Why would this be an "exception"? The basic item-based collaborative filtering described at the beginning of the article finds items that are likely to be purchased by someone who has purchased a specific item. I'm pretty sure that it's true that someone who buys a vacuum is much more likely to buy another vacuum. It may seem counterintuitive, and may not be true for you after you just bought a vacuum, but I see no reason to believe that Amazon's algorithm isn't working properly and giving Amazon a lot of value.

blacksmith_tb 9y ago
It seems like we're all saying the same things - I agree it is likely that someone who has bought a vacuum before is more likely to buy another. But to make the recommendations really shine, it should wait n months before suggesting that again, where n will vary quite a lot by product type - those are the sort of exceptions I'm talking about.

freyr 9y ago

It should not require layers and layers of exceptions to categorize products that get repeat buys (paper towels), similar buys (detective novels), or one-time buys (vacuum cleaners), and make recommendations accordingly.