What Is RankBrain?

Google’s goal is to give you better results or answers in the form of links and RichAnswers to a topic you enter in the search engine.

When you search a topic using Google, one of the third contributing factor that determines the search engine results, or SERP, is RankBrain.

RankBrain is an artifical intelligence, or AI, system that Google uses to refine its search results.

RankBrain uses machine learning technology.

RankBrain works as part of an ecosystem in Google’s overall ranking system that includes: Hummingbird, Panda, Penguin, Payday, Pigeon, Mobile Friendly, and PageRank.

It’s the comprehensive search algorithm for Google. The ecosystem is comparable to the engine of a car. The engine, like Google’s algorithm, is made up of many parts with specialized functions. RankBrain is one of the newest components of Hummingbird.

Hummingbird also contains other parts such as PandaPenguin and Payday. that are part of its search engine optimization, or SEO, space. These components are designed to fight spam.

Pigeon is designed to improve local results by reading long-tail keywords.

A long-tail keywords refers to a string of words that describe a piece of content such as article, video, image. They are highly specific, descriptive words that likely are SEO words. A long-tail keyword is easy to create. For example, take an SEO word, such as ‘nail salon,’ and add a location like a city. Your long-tail keyword would be ‘nail salon Fort Lauderdale.’ When you populate your meta tags with a long-tail keyword, your content becomes easily accessible by location to Google. Long-tail words are mobile-friendly.

Top Heavy is designed to demote ad-heavy pages in ranking. Its aim is to combat advertisements and make search engine results more accurate and organic.

Mobile Friendly is designed to reward mobile-friendly pages.

Pirate is designed to fight copyright infringement.

PageRank is designed to give pages credit in a specific way based on the links from other pages pointing at them.

RankBrain is the third-most important signal for ranking webpages which is shocking within the industry considering it was introduced in 2015.

RankBrain translates your search query in a way that prioritizes context over keywords to find the best webpages or SERP for you.

Google can see patterns between seemingly unconnected complex searches which is an element of RankBrain. Google understands how the patterns in language, words and context translate into similarity.

Google’s ability to do this allows it to better understand and anticipate future complex searches and whether they’re related to particular topics. You can see this in real time when you start entering a question into Google’s search engine. Google in turn starts anticipating your question and gives you various options (based on the Hummingbird algorithm including RankBrain) to your topic.

When this happens, it means Google has associated these groups of searches with results that it thinks applies to the topic you entered in the search menu.

Below is a crash course on RankBrain, Google’s machine-learning artificial intelligence system that’s used to refine your search engine results. The data below answers the most frequently asked questions about RankBrain.

Is RankBrain always learning?

SEO for Google Rankbrain Algorithm

RankBrain is always learning offline. RankBrain reads batches of historical searches and uses them to anticipate your search query activity. These predictions are tested, and if proven accurate, then the latest version of RankBrain goes live. The cycle is continuously testing and modifying itself.

What is machine learning?

Machine learning is the process where a computer teaches itself how to do something, instead of being taught by humans or following a detailed program.

What is artificial intelligence?

In terms of RankBrain, AI is used to refer to computer systems that are designed to learn and make connections.

What type of signals does Google use to rank a website?

Signals are things Google uses to help determine how to rank webpages. For example, the words Google reads on a webpage are considered signals. If some words are in bold, Google interprets them as a signal, too. The metrics PageRank uses to give your website a score are also considered signals. If a page is noted as being mobile-friendly, that’s another signal that’s registered.

According to Google there are over 200 major signals that are used to determine search engine results. Within those 200 major signals are up to 10,000 variations or sub-signals.

All these signals are used by various parts within the Hummingbird algorithm to figure out which pages Google shows based on your search.

What are the other two important signals used by Google?

Google says the first two signals of importance in determining a search engine result are content and links. Links remain the most important signal followed by words, but not necessarily keywords. Instead, Google is looking for quality in context not just keywords. Google uses words to interpret topic’s or queries you enter in its search engine.

How does RankBrain refine a search engine result, or SERP?

RankBrain interprets your query to find similar pages that might not have the exact words but relate to a specific topic.

Again, RankBrain does this through AI. RankBrain is classified as AI or system learning due to its ability to practice “stemming.” Stemming makes Google smarter because it allows the system to see variation in words. For example, Google understands that ‘shoes’ is a variation of ‘shoe,’ just like ‘running’ is a variation of ‘run.’

Google is knowledgable in synonyms. For example, if you search for ‘sneakers,’ Google understands that you also meant ‘athletic shoes’ and ‘running shoes.’

RankBrain also developed conceptual intelligence. What does conceptual intelligence mean? For example, Google understands that when a user types the word ‘Apple’ in its search engine, it knows that you’re referring to Apple, the technology company instead of ‘apple’ the fruit.

What about the Knowledge Graph?

The Knowledge Graph, launched in 2012, was a way that Google grew even smarter about connections between words. When it comes to search engine results, Google has learned how to search for “things not strings,” according to the internet giant.

The Knowledge Graph is a database of facts about things in the world and the relationships between them. It’s why you can do a search like ‘when was the wife of Jay-Z born’ and get an answer about Beyonce, despite the fact that you didn’t enter her name.

Strings means searching for strings of letters, such as pages, that relate to the word you enter in the search engine.

For example, if you enter ‘Bush’ in the search engine, Google understands that you mean previous US President George Bush, an actual person with connections to other people, places and things.

How’s RankBrain helping refine queries?

The method Google uses to refine queries flow back to a person who is creating content. The content is categorized either as stemming lists or synonym lists to make database connections between things.

Thus, Google’s methods were developed by people. Google reads three billion searches daily.

In 2007, a Google released data that says between 20 to 25 percent of the queries it reads has never been seen before. This means that there is a gap between between the answers you are searching for on Google and what’s readily available in terms of informative content from Google.

That number has decreased to 15 percent (of three billion queries).

Again, RankBrain is designed to help interpret questions that you ask Google either verbally (through a voice search) or manually (through text in the search engine) more precisely.

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