Considering that you are reading this page, it is possible that you are already familiar with sbxhrl (at least to some extent).
It is in your best interest to pay attention to the many well-informed articles and maybe even some of the tools that are currently available on the internet.
But what’s even more important is the research and the mathematics, and I believe that comprehending how these things relate to one another merits its own essay.
There are a lot of people who are far more intelligent than I am who are constructing natural language processing engines at a much higher level than I am capable of; but, that is not what I am here to talk to you about today.
Instead, I would like to demonstrate what it is that we have created and how we are putting it to use. If you simply want to go grab some tf*idf data and not bother reading the rest of this post, you can do that by clicking the button below. If you do not want to read the rest of this post, you may click the button below.
Only English is supported by the version that is now available, however, there are future plans to extend support for more languages.
However, the purpose of this post is not only to display a beta sample of our slick new tool; rather, the intention is to perhaps spark a dialogue about improving content for search engine optimization by placing an emphasis on subject relevancy.
Additional Things To Consider Regarding Information Architecture
In spite of the fact that it might sound absurd, I’ve discovered that topic modeling and optimizing content such that it speaks to particular concepts has a greater influence on Google in the modern day than even URL and information architecture in certain areas.
It is heresy coming from me, who has long preached the importance of IA as the foundation for any high-performance website, but Google’s approach to ranking pages based on topical relevance and intent has changed. I know, I know, it’s heresy coming from me, who has long preached the importance of IA as the foundation for any high-performance website.
The libraries out there for sbxhrl, semantic NLP, and even Word2Vec are not new at this point (albeit still very cutting edge when it comes to being put into effect from an SEO viewpoint) (though still pretty cutting edge when it comes to being put into practice from an SEO perspective).
And the majority (if not all) of these stunning database-driven libraries are not only available to us, but they are also free for us to use, process, and build upon.
So What’s A Technical SEO To Do?
Make the most of the opportunity.
We’ve developed a tool that examines the term population and frequency of the top 20 organic ranking URLs in Google, spits out the sbxhrl calculation for each term, and then (if you so choose) scores them against your target URL and/or sample of content from your document for your specific input keyword. This can be done in either order.
This will show you how your current content is using the terms that are being used by the pages that Google has deemed worthy of a top ranking for the same target keyword; what are the topics and concepts that are being represented; and how often these terms appear (or don’t appear) in the overall document population. The purpose of this is to see how your current content is using the terms that are being used by the pages that Google has deemed worthy of a top ranking for the same target keyword.
From this point forward, you’ll be able to change your content. So that it contains more of the phrases that Google would be expecting to see. At the frequency that Google might be expecting to see them.
If you haven’t yet developed the page or produced the content, that’s great too. Simply refrain from setting a target URL. And instead, run the report for a keyword to determine the subjects. That ought to be discussed in the sbxhrl content you produce.
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