Predicting the value of a search engine ranking signal

[richardmsmith]

Google was recently granted a patent with a wide range of practical applications. The patent covers how, with machine learning, they can predict a ranking signal value when the value is unknown.

Given the vast amount of content on the internet and more coming daily, Google needs to find a way to assign value to pages even if they have not been crawled and indexed. How can a page be ranked if Google hasn’t crawled it? How can Google use a new piece of content that doesn’t have any inbound links?

The methods in this patent address how the Google algorithm may address and calculate unknown factors and use them to determine where a page ranks.

We’ll discuss the possible implementations Google may be using and a couple of the problems it solves for search engine optimization specialists (SEOs). But before we start, I feel obliged to offer my standard disclaimer.

Just because something is patented, it does not mean it is incorporated into an algorithm. We need to weigh the probabilities that the patent, or parts of it, are being used with what we see around us and what makes sense. If nothing else, it gives us a glimpse into what Google is working on.