Monday 27 November 2017

How Google RankBrain Help to Get More Traffic in Your Site

How Google RankBrain Help to Get More Traffic to Your Site 

“Google using a Machine learning technology called RankBrain algorithm to deliver its search result”



What is RankBrain?

RankBrain is developed by Google. Google uses an artificial intelligent called RankBrain to help to help improve search results. Let’s see how it work with Google’s overall ranking system.
RankBrain is an Artificial Intelligent machine learning system that’s used to help process its search result.

What is Machine Learning?


Machine learning is where computer teaches itself how to work and to do something, rather than being taught by humans.

What is Artificial Intelligent?


True artificial intelligence, or AI for short, is where a computer can be as smart as a human being, at least in the sense of acquiring knowledge both from being taught and from building on what it knows and making new connections.
True AI exists only in science fiction novels, of course. In practice, AI is used to refer to computer systems that are designed to learn and make connections.
How’s AI different from machine learning? In terms of RankBrain, it seems to us they’re fairly synonymous. You may hear them both used interchangeably, or you may hear machine learning used to describe the type of artificial intelligence approach being employed.

Name of the Google's Search Algorithm



Name of Google Algorithm is Hummingbird, as we reported in the past. For years, the overall algorithm didn’t have a formal name. But in the middle of 2013, Google overhauled that algorithm and gave it a name, Hummingbird.

RankBrain with Google's Algorithm

Hummingbird also contains other parts with names familiar to those in the SEO space, such as PandaPenguin, and Payday designed to fight spam, Pigeon designed to improve local results, Top Heavy designed to demote ad-heavy pages, Mobile Friendly designed to reward mobile-friendly pages and Pirate designed to fight copyright infringement.

Page Rank

PageRank is part of the overall Hummingbird algorithm that covers a specific way of giving pages credit based on the links from other pages pointing at them.
PageRank is special because it’s the first name that Google ever gave to one of the parts of its ranking algorithm, way back at the time the search engine began, in 1998.

Signals


Signals are things Google uses to help determine how to rank web pages. For example, it will read the words on a webpage, so words are a signal. If some words are in bold, that might be another signal that’s noted. The calculations used as part of PageRank give a page a PageRank score that’s used as a signal. If a page is noted as being mobile-friendly, that’s another signal that’s registered.
All these signals get processed by various parts within the Hummingbird algorithm to figure out which pages Google shows in response to various searches.
Google has fairly consistently spoken of having more than 200 major ranking signals that are evaluated that, in turn, might have up to 10,000 variations or sub-signalsGoogle says is the third-most important factor for ranking web pages. 

Work of RankBrain

RankBrain is mainly used as a way to interpret the searches that people submit to find pages that might not have the exact words that were searched for.

Google has found pages beyond the exact terms someone enters for a very long time. For example, years and years ago, if you’d entered something like “shoe,” Google might not have found pages that said “shoes,” because those are technically two different words. But “stemming” allowed Google to get smarter, to understand that shoes is a variation of shoe, just like “running” is a variation of “run.”

Google also got synonym smarts, so that if you searched for “sneakers,” it might understand that you also meant “running shoes.” It even gained some conceptual smarts, to understand that there are pages about “Apple” the technology company versus “apple” the fruit.

Knowledge Graph

The Knowledge Graph, launched in 2012, was a way that Google grew even smarter about connections between words. More important, it learned how to search for “things not strings,” as Google has described it.
Strings mean searching just for strings of letters, such as pages that match the spelling of “indira Gandhi.” Things means that instead, Google understands when someone searches for “indira Gandhi,” they probably mean central figure of the Indian National Congress indira Gandhi, an actual person with connections to other people, places and things.
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 father of indira Gandhi born” and get an answer about Jawaharlal Nehru as below, without ever using her name:
RankBrain with Refine Queries
The methods Google already uses to refine queries generally all flow back to some human being somewhere doing work, either having created stemming lists or synonym lists or making database connections between things. Sure, there’s some automation involved. But largely, it depends on human work.
The problem is that Google processes three billion searches per day. In 2007, Google said that 20 percent to 25 percent of those queries had never been seen before. In 2013, it brought that number down to 15 percent, which was used again in yesterday’s Bloomberg article and which Google reconfirmed to us. But 15 percent of three billion is still a huge number of queries never entered by any human searcher — 450 million per day.
 Among those can be complex, multi-word queries, also called “long-tail” queries. RankBrain is designed to help better interpret those queries and effectively translate them, behind the scenes in a way, to find the best pages for the searcher.
As Google told us, it can see patterns between seemingly unconnected complex searches to understand how they’re actually similar to each other. This learning, in turn, allows it to better understand future complex searches and whether they’re related to particular topics. Most important, from what Google told us, it can then associate these groups of searches with results that it thinks searchers will like the most.
Google didn’t provide examples of groups of searches or give details on how RankBrain guesses at what are the best pages. But the latter is probably because if it can translate an ambiguous search into something more specific, it can then bring back better answers.
This article's reference is: https://searchengineland.com/





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