Google Clarifies How Helpful Content System Works - Search Engine Journal

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Google SearchLiaison cleared up a confusing passage in their Helpful Content System guidance that seemingly had the potential to cause inadvertent issues for innocent publishers.

Helpful Content System

Google’s Helpful Content System is based on a machine learning model that uses classifiers to generate a signal that is then used by Google’s ranking system to weed out low quality content.

A classifier is an algorithm in a machine learning model that assigns a label to an input. In the context of the Helpful Content System, the machine learning model is assigning a label to website content, which is turn generates a signal, like a thumbs-down.

That signal is also weighted, which means that a site with just a little unhelpful content gets a smaller thumbs down than a site with a lot of unhelpful content which would get a larger thumbs down.

The Helpful Content System generates a signal, which is one of hundreds or thousands of other signals used to rank a site (like links, relevancy, etc.).

Google Guidance Unintentionally Opaque

Google updated their guidance for the Helpful Content System during the last Helpful Content System in order to help add clarity of what this signal was so that...

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