Will Google’s Rankbrain Make Marketers Change Their Ways Again?

Google recently announced that it is using another layer to its ranking algorithm, called RankBrain which will focus on machine learning and will work towards improving its concept of semantic search which shows you direct results on searching instead of giving a link.

RankBrain will be used to sort through the billions of pages it knows about and find the ones deemed most relevant for particular queries. A couple of years ago, Google had told us that nearly 500 million unique search were made everyday- “questions” that they had never been seen before. It summed upto 15% of all the search made on Google in a day.

RankBrain uses artificial intelligence to embed vast amounts of written language into mathematical entities called vectors that the computer can understand. If RankBrain identifies a word or phrase for the first time, the machine can make a guess as to what words or phrases might have a similar meaning and filter the result accordingly, making it more effective at handling never-before-seen search queries. In other words, it’s more like adding common sense to machines.

To read in details about Google’s Thought Vectors project, Artificial Neural Networks and Inceptionism, click here.

“It’s one of the “hundreds” of signals that go into an algorithm that determines what results appear on a Google search page and where they are ranked,” said Corrado Greg Corrado, a senior research scientist with the company. Within a few months of its employment, RankBrain has become the third-most important signal contributing to the result of a search query, he stated.

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Patent of Larry Page’s original PageRank algorithm which was assigned to Stanford University in 1997 and was exclusive to Google till 2011 will expire in 2017. However, over the years Google has improved it’s original algorithm and is currently using Hummingbird which they started around September 2013, introducing us to semantic search. Updates made to Hummingbird till date are -Panda, Penguin 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.

Machine learning has become an inextricable part of search algorithms for quite some time now. Not long ago, Apple announced its entry into search and machine learning with ‘Spotlight’, and Bing too has been showing a keen interest in it with its project ‘Distill’. With time, these algorithms are getting smarter, learning and improving data connections on its own, thereby making SEO professionals’ job trickier.

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