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If you stand back and think about how these schemes operate, you wouldn't actually _need_ ML to solve it. Step 1 is getting a list of new products that are rec

If you stand back and think about how these schemes operate, you wouldn't actually _need_ ML to solve it. Step 1 is getting a list of new products that are receiving a higher than expected number of 5-star reviews Step 2, add it to a list of similar products. Step 3, find accounts that all happen to purchase the same products in the same order. Step 4, ban accounts and sellers.

sidlls 7y ago
That is a very simple algorithm! It’s also something the sort of people who do this will overcome relatively quickly. Automated or systemic attacks and mitigation is a war of escalation.
martin_a 7y ago
> If you stand back and think about how these schemes operate, you wouldn't actually _need_ ML to solve it. As Machine Learning is just a fancy way of doing statistics, you will totally not need it for this.
luckylion 7y ago
step 5: I now have a great way to boot competitors off of your marketplace.
zadkey 7y ago
"Step 1 is getting a list of new products that are receiving a higher than expected number of 5-star reviews" What is higher than the expected number of 5-star reviews? Don't those numbers vary widely depending on product category, brand, and newness of the product? How does that work for things that fit into more than 1 product category?
- julianlam 7y ago
  > What is higher than the expected number of 5-star reviews? That's left as an exercise for the reader ;) But you could simplify this to new products, which if ungamed, would probably follow a predictable curve of discovery, as opposed to a games "instant 5 star" rating.
  - throwaway99191 7y ago
    LMAO no one is buying the "exercise" excuse. You tried to look smart and failed miserable. There are so many problems with your plan it's embarrassing.
frandroid 7y ago
You can do all this manually, but really you just described a form of machine learning.

sidlls 7y ago

That is a very simple algorithm! It’s also something the sort of people who do this will overcome relatively quickly. Automated or systemic attacks and mitigation is a war of escalation.

martin_a 7y ago

> If you stand back and think about how these schemes operate, you wouldn't actually _need_ ML to solve it. As Machine Learning is just a fancy way of doing statistics, you will totally not need it for this.

luckylion 7y ago

step 5: I now have a great way to boot competitors off of your marketplace.

zadkey 7y ago

"Step 1 is getting a list of new products that are receiving a higher than expected number of 5-star reviews" What is higher than the expected number of 5-star reviews? Don't those numbers vary widely depending on product category, brand, and newness of the product? How does that work for things that fit into more than 1 product category?

julianlam 7y ago
> What is higher than the expected number of 5-star reviews? That's left as an exercise for the reader ;) But you could simplify this to new products, which if ungamed, would probably follow a predictable curve of discovery, as opposed to a games "instant 5 star" rating.
- throwaway99191 7y ago
  LMAO no one is buying the "exercise" excuse. You tried to look smart and failed miserable. There are so many problems with your plan it's embarrassing.

frandroid 7y ago

You can do all this manually, but really you just described a form of machine learning.