4 ms·

Indeed. My mind races: something like assigning super-distinctive words prime numbers and multiplying them in a paragraph, and doing a lookup on it to see if

• nl 16y ago
  That algorithm would find duplicate content, which Google has done a decent job detecting for a while. The new update was about low-quality content. Thinking of an algorithmic way to detect that isn't easy (obviously!). I guess I'd be looking at adapting things like http://en.wikipedia.org/wiki/Flesch%E2%80%93Kincaid_readability_test http://en.wikipedia.org/wiki/Flesch%E2%80%93Kincaid_readabil... somehow, so it wouldn't penalize either easy-to-read or difficult-to-read but would look at the density of harder-to-read content vs easier-to-read fluff. Or something!
  • benologist 16y ago
    I'm not sure it would be that hard for Google to identify the crap sites - when you go to one you either click your back button or out through the adsense that usually dominates/perfectly blends with the content anyway, Google is catching that bounce rate damn near 100% of the time.
• Dn_Ab 16y ago
  The article is actually quite forthright. Singhal implies that the core of this uses some form of machine learning. Looks like a binary good-bad classifier that can give confidence or a probability in its predictions. Negative ratings have a higher threshold. I'm thinking what is more important than classifier is what features are chosen. I bet the breakthrough was a clever way to choose or identify these features.