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The guide announced by Google aims to understand the most important search results ranking systems. Thaspol – stock.adobe.com

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Google presents a guide to search result ranking systems

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In a post, Google announces the availability of a new guide that aims to familiarise designers with the search results ranking systems. The guide lists the systems currently used in Google search, with a brief explanation of each. In addition, Google is introducing new terminology by distinguishing between “ranking systems” and “updates”.

“In the past, the term “update” has often been used as the name of a particular ranking system, especially when a new system was rolled out,” Google explains, “In the future, we will be more specific in our wording to differentiate between ‘systems’ and ‘updates’. We’ll still have terms like “helpful content update” or “product reviews update”, but where possible we’ll explain them as updates to the respective systems, such as the “helpful content system” and “product reviews systems”. We will also update our help pages to reflect this change in terminology over time.

Thus, it should be noted that a “system” is constantly running in the background, while an “update” refers to a one-time change to the ranking systems. For example, the Helpful Content Update system is always running in the background when Google provides search results, although it may receive updates to improve its performance. Other examples of ad-hoc changes to ranking systems are core algorithm updates and spam updates.

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Current and obsolete filing systems

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According to the guide, the following are the ranking systems currentlyused by Google, some of which are multiple and others unique:

BERT (Bidirectional Encoder Representations from Transformers): This allows Google to understand how combinations of words can express different meanings and intentions.
Crisis Information Systems: These systems are responsible for providing specific sets of information in times of crisis, whether it be personal crisis situations, natural disasters or other widespread crisis situations in the case of related searches.
Deduplication systems: These systems aim to provide the most relevant results to avoid unnecessary duplication in a search.
Exact Domain Matching System: This system ensures that Google does not give too much credit to websites whose domain names exactly match a query.
Information freshness systems: This set of systems aims to display more recent content for specific queries. For example, if a user is looking for a movie that has just been released, he/she will probably want recent reviews rather than older articles from the beginning of the production.
Helpful Content System: This system is designed to ensure original and helpful content written by people for people in search results, rather than content designed primarily to generate search engine traffic.
Link analysis and PageRank systems: these systems determine what pages are about and which ones might be most useful in response to a query, based on how pages are linked together.
Local information systems: these systems aim to identify and highlight local news sources where relevant to a query.
MUM (Multitask Unified Model): This AI system is capable of both understanding and generating language. It is used in particular to improve featured search snippets and is not used for general search ranking.
Neural matching: This AI system is used by Google to understand representations of concepts in queries and pages, in order to match them to each other.
Original content systems: This set of systems ensures that Google displays original content first in search results, including original reports, before sites that merely quote it/them.
Removal-based demotion systems: These systems aim to demote websites that are subject to a high volume of content removal requests from the search results.
Page Experience System: a system that evaluates, through various criteria, whether a web page provides a good user experience.
Passage Ranking System: an AI system used by Google to identify individual sections or “passages” of a web page to better understand the relevance of a page to a search query.
Product reviews system: this system aims to give more visibility to high quality product reviews and content that provides relevant analysis, written by experts or enthusiasts who know the subject well.
RankBrain: an AI system that helps Google understand how words relate to concepts, so it can better deliver relevant content even if it does not contain all the exact words used in a search.
Trustworthy information systems: these systems help display trustworthy information, bringing up authoritative pages, demoting poor quality content and promoting quality journalism.
Site diversity system: a system that prevents Google from showing more than two lists of web pages from the same site in the top results.
Spam detection systems: a system that addresses content and behaviour that violates Google’s spam policies.

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Google also points out that these systems are now obsolete:

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Hummingbird,
Mobile-friendly ranking system,
Page speed system,
Panda system,
Penguin system,
Secure site system.

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Graphic trends for 2023 © Venngage

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Other articles

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What is an authentication token?

An authentication token (or security token) is a hardware or software device that a user needs to access an application or network system more securely.

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guide to understand search results

With the release of its guide to the visual elements associated with search results, Google presents the components of a results page in images and tells us a little more about the form of these elements, their names and their usefulness. This is of interest to those who want to learn about SEO…

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Graphic trends 2023

Venngage, a website for creating visuals and infographics, lists the graphic trends that will stand out in 2023. The objective? Anticipate your marketing strategy and stand out with trendy and innovative graphic creations.

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5 key predictions for the web and social networks in 2023

Once again this year, We are Social has published its Think Forward 2023 report entitled “Fragmented Futures”, which examines social behaviour and highlights the social media predictions for the next twelve months.

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How to prepare for a Google update

Google is constantly making changes to the way its search engine works. Sometimes these changes are made at a breakneck pace: in 2018, it made over 3,200 updates!

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Web 3.0, the new internet

First there was web1 – aka the internet we all know and love. Then there was web2, the user-generated web heralded by the arrival of social networks. Now, everywhere we look, people are talking about web3 (or sometimes web 3.0)

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Google presents a guide to search result ranking systems

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How to detect text generated by an AI like ChatGPT

Artificial Intelligence is currently the subject of much discussion. Their arrival on the general public market is subject to controversy and everyone has found a way to use them in their own way. Nevertheless, some of its uses are subject to abuse, particularly in the creation of text.

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