Google Publishes Guide To Current & Retired Ranking Systems via @sejournal, @MattGSouthern

A new guide to Google's ranking systems will keep you informed about which systems are used to rank search results and which ones are retired. The post Google Publishes Guide To Current & Retired Ranking Systems appeared first on...

Google Publishes Guide To Current & Retired Ranking Systems via @sejournal, @MattGSouthern

A new guide from Google will help you stay informed about which ranking systems Google uses and which ones are retired.

Google Publishes Guide To Current & Retired Ranking Systems

A new guide to Google’s ranking systems will keep you informed about which systems Google uses to rank search results and which ones are retired.

Additionally, Google introduces new terminology in its latest guide, distinguishing between ranking “systems” and ranking “updates.”

A system, such as RankBrain, is constantly running in the background. An update, on the other hand, refers to a one-time change to ranking systems.

For example, the helpful content system is always running in the background when Google delivers search results, though it can receive updates to improve how it functions.

Core algorithm updates and spam updates are other examples of one-time changes to ranking systems.

Now that we’re on the same page with Google’s new terminology, let’s look at the highlights in Google’s guide to ranking systems.

Current Google Ranking Systems

Here is the list, in alphabetical order, of Google’s ranking systems that are currently operational.

BERT: Short for Bidirectional Encoder Representations from Transformers, BERT allows Googe to understand how combinations of words can express different meanings and intent. Crisis information systems: Google has systems in place to provide specific sets of information during times of crisis, such as SOS alerts when searching for natural disasters. Deduplication systems: Google’s search systems aim to avoid serving duplicate or near-duplicate webpages. Exact match domain system: A system that ensures Google doesn’t give too much credit to websites with domain names that exactly match a query. Freshness systems: A system designed to show fresher content for queries where it would be expected Helpful content system:  A system designed to better ensure people see original, helpful content, rather than content made primarily to gain search engine traffic. Link analysis systems and PageRank: Systems that determine what pages are about and which might be most helpful in response to a query based on how pages link to each other. Local news systems: A system that surfaces local news sources when relevant to the query. MUM: Short for Multitask Unified Model, MUM, is an AI system capable of understanding and generating language. It improves featured snippet callouts and is not used for general ranking. Neural matching:  A system that helps Google understand representations of concepts in queries and pages and match them to one another. Original content systems: A system to help ensure Google shows original content prominently in search results, including original reporting, ahead of those who merely cite it. Removal-based demotion systems: Systems that demote websites subject to a high volume of content removal requests. Page experience system: A system that assesses various criteria to determine if a webpage provides a good user experience. Passage ranking system: An  AI system Google uses to identify individual sections or “passages” of a web page to understand better how relevant a page is to a search. Product reviews system:  A system that rewards high-quality product reviews written by expert authors with insightful analysis and original research. RankBrain:  An AI system that helps Google understand how words are related to concepts. Allows Google to return results that don’t contain exact words used in a query. Reliable information systems: Google has multiple systems to show reliable information, such as elevating authoritative pages, demoting low-quality content, and rewarding quality journalism. Site diversity system: A system that prevents Google from showing more than two webpage listings from the same site in the top results. Spam detection systems: A system that deals with content and behaviors that violate Google’s spam policies.

Related: A New Era Of Google Search: What It Means For SEO

Retired Google Ranking Systems

The following systems are noted for historical purposes. These have been incorporated into other systems or made part of Google’s core ranking system.

Hummingbird: A significant improvement to Google’s ranking systems that rolled out in 2013. Systems have evolved since then, Google says. Mobile-friendly ranking system: A system that prefers content rendered better on mobile devices. It has since been incorporated into Google’s page experience system. Page speed system: A system introduced in 2018 that gave preferences to content that loaded fast on mobile devices. It has since been incorporated into Google’s page experience system. Panda system: A system introduced in 2011 that preferred high-quality and original content. It became part of Google’s core ranking systems in 2015. Penguin system: A system introduced in 2012 that demoted websites with spammy linkbuilding practices. Secure sites system: A system introduced in 2014 that preferred websites secured with HTTPS. It has since been made part of Google’s page experience system.

Source: Google

Featured Image: Koshiro K/Shutterstock

SEJ STAFF

Matt G. Southern

Senior News Writer at Search Engine Journal

Matt G. Southern, Senior News Writer, has been with Search Engine Journal since 2013. With a bachelor’s degree in communications, ...

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