Stay with us in this article to learn about another Google algorithm and how it works.

What is Google’s Rankbrain algorithm? The Rank Brain algorithm is part of the core Google algorithm that uses machine learning (the ability of machines to learn from input data) to determine the most relevant results to the searched queries. Before RankBrain, Google used its base algorithm to determine the results displayed for a search query. After Google’s Rank Brain algorithm, it is believed that the desired query enters an interpretive model that can consider factors such as the searcher’s location, personalization, and query words to determine the searcher’s true intent. By detecting true intent, Google can provide more relevant results. The machine learning aspect of RankBrain is what sets it apart from other updates. To teach the Rank Brain algorithm to provide useful search results, Google first feeds it data from various sources. The algorithm then begins its work from here and teaches itself by calculating over time to match different signals with different results to sort the search engine rankings based on these calculations.

Understanding Google’s Rank Brain Algorithm

To get a true picture of Google’s Rank Brain algorithm, it’s better to put yourself in Google’s place, trying to find the true intent of a search engine query, for example, “Olympics location”.

What is the real purpose of this search? Does the searcher want to know about the summer or winter Olympics? Does he mean the Olympic games that have been held in the past or the games that will be held in a few years? Does the searcher want to be at the Olympics, sitting in their hotel room and looking for directions to the opening ceremony? Could it be that he is looking for historical information about the location of the first Olympic Games in ancient Greece?

Now imagine that when answering this query, all you have at your disposal are simple algorithmic signals such as the quality of the content or the number of links that a piece of content has earned to rank for the search results. Imagine that the Winter Games were held in Sochi, Russia last month, and the Sochi Olympics website received millions of links to its content about the past event. If your algorithm is simplistic, it might only display results related to the Sochi Games because they received the most links… even though the searcher was hoping for the location of the next Olympic Winter Games in PyeongChang. Know South Korea.

In this complex but common situation, the capacity of Google’s Rank Brain plays a vital role. It is only by having the ability to do mathematical calculations based on the patterns that the machine learning algorithm has noticed in the searcher’s behavior that Google can determine the true intent, for example, what most people searching for “Olympic venue” want to know. Where will the next competitions (both winter and summer) be held? Therefore, in this case, a responsive Google box along with the location of future games can solve the needs of the majority of people in this field.

While the above box can identify the true intent of most searches about the Olympic location, there are notable exceptions that Google should consider. For example, if a search is made by a user in an Olympic city (such as PyeongChang) during the week of the Games, Google may provide directions to the location where the opening ceremony is held. In other words, signals such as user location and content recency are taken into account to interpret intent and provide results that are more likely to satisfy searchers.

RankBrain is a project in progress, to perfect Google’s interpretation of searcher intent over time through machine learning.

Due to the scope and detailed impact that RankBrain has on how Google’s core algorithm works is still not fully fleshed out, one of the best ways to understand how RankBrain works is to see how often Once Google gives an answer to your various queries that satisfies you, it is possible. How often do they correctly interpret your search intent?

The impact of the Rank Brain algorithm on SEO

Depending on the sophistication and modernity of your personal SEO skills, RankBrain can make small or large changes in your theories and activities. Bill Slawski, one of the experts in this field, gives the following example about the importance of the Rank Brain algorithm for the search environment:

“To a rider, a horse is a big 4-legged animal, to a carpenter, a horse has 4 legs, but it doesn’t live on a farm or eat hay, to a gymnast, a horse is something you jump over. The concept becomes important with Rank Brain, and making sure you get the concept is probably the key to optimizing this machine learning solution.”

3 essential concepts in Rank Brain

1- Different ranking signals are applied to different queries

Before the Rank Brain algorithm, evaluating page optimization by checking all the traditional signals (link diversity, content depth, keyword matching, etc.) might seem reasonable. After Rank Brain, SEO should determine the content model that best meets the user’s needs. For something like a flash storm, you’re just looking at more content than links might have. For something like Native American music history, you rely on the depth of content and possibly other relevant topics your domain covers to signal your credibility. Know that the machine learning algorithms that drive RankBrain match signals with search intent, and SEO should do the same.

2- Signals are applied to your site’s credibility

SEO seeks to build your brand’s credibility as a trusted source for search engines and human users to provide a unique experience. The benefits of building such a reputation can include getting good rankings for keywords you care about. Should your brand build its credibility based on freshness, depth, variety of incoming links, high user engagement, or other signals? The answer depends on the topics you are covering. (For example, live sports scores or an online Spanish course)

Do the searches you hope to rank for require quick, concise answers or in-depth details? Over time, your domain should build its credibility based on the signals it wants to provide and realize that RankBrain creates an environment where your brand can provide a specific model of content that addresses a specific need. to be recognized.

3- One keyword per page is completely dead

You probably know that making a page for “skim”, another for “skims”, another for “kitchen skimmer”, another for “pancake turner” and another for “metal skimmer” is like a tired horse that has to be Let’s get rid of suffering. Modern SEO combines all these sentences (along with their links) into a sequenced piece of content that has natural dialect and different keywords that reflect the way humans talk and search. This is not new news for SEOs, but the emergence of Rank Brain shows the knowledge of focusing on the general concept of keywords along with comprehensive content instead of separating different pages to cover variables such as “widgets” and “widgets”.


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