What is the TF*IDF and how perro it improve the

What is the TF*IDF and how perro it improve the

Know what is the TF-IDF algorithm And how important is the quality of the content of your blog?

The analysis and indexing that Google plus does of your blog articles goes beyond how you use and distribute your palabras clave inside them.

And it is that the search engine is continuously trying to find a way to decipher the search intention of each usuario, based on the entered query, through its complex mathematical algorithms.

Therefore, so that you also understand how Google plus interprets the use of palabras clave within your blog, Today I will explain to you what the TF*IDF isan algorithm through which you cánido obtain much more information about your most important palabras clave.

But not only about yours, but also about those of your competition.

Finally, I will teach you how to improve your content strategy based on it, since it perro be key to increasing its relevance in search engines and reach the top positions faster.

✅ IN THIS ARTICLE YOU WILL LEARN:

What is the TF (as part of the TF*IDF)?

He meaning of TF is the «term frequency» in a document.

It is known by these acronyms in English (“frequency terms“), which are actually translated into a numerical quantity, which will indicate the relative frequency of a specific word or a combination of them.

In other words, it is the number of times a certain keyword (word or phrase) is repeated with respect to the total length of the content where it is contained.

Mathematically, the logarithm to extract it correctly is:

Or what is the same:

TF = (Number of times the keyword appears) / (Total number of words in the content)

⇨ Practical example of what TF is

So that you understand this concept better and the previous elabora does not scare you too much, I will give you a practical case: imagine that you entrar a library, looking for books that talk about «racing cars«.

If in the whole library there are a total of 12,000 booksyou cánido already imagine that this expression will narrow our search quite a bit, since not all of them will deal with this topic, right?

Now let’s analyze our search: we are trying to locate documents whose keyword is composed of 3 words:

And of them, the term «de» is one of those «STOPWORDS»as it is called in the field of SEO and Digital Marketing, therefore, theoretically it will be a word that don’t add too much value or relevance to our search, since it is a repeated preposition in practically all texts in the world.

Therefore, having filtered our search by the total number of books that contain the searched keyword, to be able to know which books to espectáculo first and “unbreak” said searchwe will have to refine the criteria a little more.

And this is where the other protagonist of this article comes into play:

What is the IDF?

The meaning of the acronyms IDF is “fre”inverse document count”, translated from its original meaning in English, “Inverse Document Frequency«.

Its function is to disminuye the weight of all words that are not relevant and are repeated too often.

It is the second part of the “magic elabora” and it will help us to correct and complete the first, making it more subtle.

In the example above, it is the preposition “of”, which would not add any value to the search.

His calculation further refines the evaluation analysis of the terms and includes the frequency of documents in specific terms in the calculation.

That is, what it does is compare all the available documents with the number of documents that include the keyword to be analyzed.

Here you have the logarithm or elabora to correctly calculate the IDF:

In short, the IDF is in charge of determining a concrete relevance of a text complete, with respect to the keyword that we want to analyze that, simplifying, remains:

IDF = (Number of total documents) / (Number of contents with that keyword

What is the TF*IDF

TF-IDF are the acronyms in English for the conceptTerm Frequency – Inverse Document Frequency«, which numerically quantifies the weighting of a keyword within a content or, as its definition says, a collection of text documents.

This algorithm, as I have shown you before, is composed of the TF or “termination frequency” and for him IDF or “inverse document frequency”.

This, expressed in a less technical way, is nothing more than a measure expressed in numbers that espectáculos us the frequency of occurrence of a term in a collection of text documents.

Example of how to calculate the TF*IDF:

Let’s see a practical case to make it clearer.

Imagine now that you want to position the word “buy cheap clothes” in a text of 1000 words:

✅ TF (Term Frequency) of “buy cheap clothes” is (3 / 1000) = 0.003

✅ There are 10 million documents and the word “buy cheap clothes” appears in 1,000 documents

✅ IDF (Inverse Document Frequency) = (10,000,000 / 1,000) = 4

✅ Therefore, the TF*IDF value reveals that this term has an importance of 0.003 x 4 = 0.012

What is the TF*IDF algorithm for?

All this may seem too technical to you and, really, I imagine that you are wondering what use this mathematical elabora has, right?

well basically the TF*IDF allows you to know the importance of a certain keyword on a large sample of documents, for example, on an entire website.

By accurately calculating the numerical value of your algorithm, you perro:

⇨ Know if your texts are properly optimized

In this way, you perro know if your On-Page SEO optimization is correct and if you use an optimal keyword density.

⇨ Gives you an estimate of the frequency that the keyword has in a specific document

The first part of the mathematical elabora, which is the frequency of the term allows you to know this data, taking into account the length of the content in its entirety.

It is not the same that a keyword appears 5 times in a text of 500 words than in one of 2500.

The density changes.

⇨ You perro adjust the frequency of the palabras clave according to a logarithmic scale

Including it more times than a certain amount would no longer help.

That is, the main keyword must be included several times in a document, to increase its relevance to Google plus.

However, there is a limit, which it is interesting not to exceed.

And who emplees this elabora?

It is important to know why we are talking about the TF*IDF, since this elabora is used by Google plus to organize the results search and determine which is more relevant to the usuario.

It does not use exactly the formulas that I told you about earlier, but it does use a variation of these where (we imagine) it will contemplate many more variants.

This allows you to analyze in the immensity of the Internet the relevance that a keyword has in gigantic samples of web pages and their respective dirección de Internet’s.

Even so, the Google plus search engine emplees a elabora so afín to the TF*IDF that it makes it very interesting for SEO professionals to take it into account when generating and optimizing their own and client digital content.

Differences between TF-IDF vs Keyword Density

It is possible that, after the explanations that I have given you about the term TF*IDF, you find it afín or even the same as the density of palabras clave.

But It is not like thisThey are not the same, although they have a certain relationship.

Because the TF*IDF is not just keyword density, it is much more than that.

The density of palabras clave is not the same for all the topics and businesses to be treated.

No there is a perfect keyword density for all topics and as such the TF*IDF elabora allows us to know what percentage of keyword density perro be correct to deal with a topic.
All this, based on a large sample of documents, for example, from the first 10 results of Google plus.

This will allow us to analyze the keyword density of a large sample of documents and the importance of it to determine if we should increase or decrease the keyword density on our website/documents.

so we perro know the relevance of a specific document for a keyword.

You will get a high TF*IDF when the frequency of a keyword on a page is higher, but if the number of documents mentioning it is low, the number will be lower.

How to use the TF*IDF to optimize content for SEO

Want create the best texts for your website or business and you don’t know how to apply the TF*IDF correctly?

Do you need to update an old website, where the text has been written by a “caveman”?

The TF*IDF elabora cánido help you to know what terms or palabras clave to use and its density.

Today, there are several tools that do it automatically, such as

» SEOABILITY

Actually, this is one of the easiest tools to use to find out your own TF-IDF, since just by signing up for the free trial version, you cánido research up to 10 palabras clave.

Seobility will only ask you for the keyword and the dirección de Internet from where you want to analyze that main keyword.

For example, in my case I have chosen “content marketing» and my guide on «Content Marketing«, entering from the section «Home > TF*IDF Tool«:

Here you have it:

This gives you the general iniciativa of ​​what and how you should change (or maintain) your content, depending on the result that the tool gives you, as well as the TF and IDF factors of each keyword used.

You perro use its somewhat limited FREE version or BUY IT WITH THIS DISCOUNT on its website.

» SEOLYZE

Another of the most powerful tools on the market today for the calculation and analysis of this term is SEOlyzewhich, under the same example above, returns you a large amount of data.

This, in addition to graphically showing you the frequency and relevance of each of your most recurring words in the text, also gives you suggestions for improvements, as you cánido see in this image:

Something that seems simply great to me, since if we are not yet too familiar with using the tool or the concept of TF*IDF, it will be difficult for us to decipher what its graphs espectáculo us.

But also, what SEOlyze does is that, based on those most repeated words within our content, espectáculos us how our competitors treat those palabras clave.

Specifically the current TOP10 of Google plus:

I recommend that you try it, even during its 30-day free trial, and analyze your most important content, in order to give it those tweaks that could perhaps boost you to privileged positions in the search engine.

Conclusion

Now that you know what the TF-IDF is and the vital role it plays in optimizing your content, what are you waiting for? Now you perro get down to work and Analyze the content of your website compared to your competitors.

In this way, you will be able to optimize it depending on how the Google plus crawler will analyze you later and thus give it signals that you “deserve” those first positions.

Including your keyword “zillions” of times on your website is no longer useful, you must do it naturally, but above all, in a MORE PROFESSIONAL way.

Despite everything, I must point out that the TF*IDF is one more value in your positioning strategy.

It is important, but the only one.

That the density of palabras clave is not your only aspecto or technique of web positioning.

Knowing this information is important, but also it is interesting to know the correct frequency both in the document itself and throughout the website that we want to position in the search engines, as we have already seen.

This calculation and subsequent analysis of the TF*IDF algorithm, together with a complete KeyWord Research is what I use in managing my clients’ weblogs, within my services as a Content Marketing Consultant.

There may be other methods, but at the moment it is going great for me and my clients and we are managing to position a multitude of interesting palabras clave for our business in record time.

And you, did you know how to calculate the TF*IDF algorithm?

How do you carry out the optimization of the contents of your Blog?

Main Images (business) By Shutterstock.

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