Google's Gary Illyes Explains How RankBrain Works
Google's Gary Illyes has provided a matter-of-fact explanation of how the RankBrain algorithm works.
How Google RankBrain Works, Internal URLs & Canonicalization, Mobile Search
November 6, 2015 SEO Theory Hangout
Michael Martinez of Reflective Dynamics, Inc. and Kent Yunk of Roaring Pajamas SEO talk about search engine optimization and Web marketing.
* How the Google RankBrain algorithm works
* How to use internal URLs for SEO
* Managing canonicalization
* How mobile query data differs from desktop query data
Google has lost the syncronization between the audio and the video but the entire session was recorded. You should probably just listen to the audio. Sorry.
Google’s Rankbrain – How it works and how to optimize for it
In this video,
We will talk about Rankbrain Google’s first official AI system about which Google says that it is 3rd most influential ranking factor.
We will learn about it history, working and how we can use it for our advantage
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Hope this will be a useful video for you all.
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What is Google’s RankBrain? Listen to Search Talk Live
We go over the recent announcement About the Google’s algorithm Called RankBrain Googles artificial intelligent , Self Learning Algorithm. Learn what the RankBrain algorithm works and how it works with Hummingbird, Panda, Penguin and all the other algorithm to improve the search results.
http://www.searchtalklive.com
How Google’s PageRank Algorithm Works
Google’s PageRank algorithm is one of the most important algorithms on the Internet. The algorithm attempts to rank pages according to their importance. But what does it mean for a web page to be “important”? In this video, we explore the “random surfer” model, which allows us to calculate a page’s PageRank by simulating a random surfer who browses the web one page at a time.
0:00 PageRank
1:39 Random Surfer Model
3:40 Damping Factor
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Spanning Tree is an educational video series about computer science and mathematics. See more at https://spanningtree.me
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Spanning Tree is created by Brian Yu. https://brianyu.me/
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