Semantic positioning in Google

Semantic positioning in Google

We spend so much time trying to seduce Google that we often forget that those who really do the searches in the search engine are people.

Algorithms in search engines can solve many searches and adapt more and more to the way we find what we are looking for, but they still differ a lot from how a person thinks.

For a long time, work has been done on artificial intelligence that makes the machine have automatic learning, this artificial intelligence adapts to search engines to refine their search techniques.

What is semantic search?

The word “semantics” refers to the meaning or essence of something. Applied to search, “semantics” essentially refers to the study of words and their logic. Semantic search seeks to improve search accuracy by understanding the searcher’s intent through contextual meaning.

Through the principle of correlation, synonyms, and natural language algorithms, semantic search provides more interactive search results by transforming structured and unstructured data into an intuitive and responsive database.

Semantic search results in a better understanding of searcher intent, the ability to extract answers, and offers more personalized results.

Why do search engines chase semantics?

From the perspective of a search engine or also called a spider, what it is looking for is a deeper understanding of the user’s intent, and a more natural search language, that is, conversational.

There are 7.4 billion people in the world, each with their education and culture, their lifestyle and a different thought, this shows the difficulty that a search engine can have to organize, structure and expose these semantic connections.

One of the ways that Google helps to approach semantic search is by identifying and disqualifying low-quality content. Methods that identify nonsense phrases, the stuffing of pages with keywords, the frequency of use of certain terms try to ensure that websites have quality content, penalizing those who do not comply with it or try to spam.

The use of semantics and entity-based search makes it possible for engines to gain a better understanding of what users want. Let’s see an example to understand it:

By specifying a long-tail search, that is, contextually indicating what we want in a colloquial way, it has indicated exactly what we wanted in the first result.

However, if we search only for a name, it will give us all the information it finds. In this case, the search engine does not know how to identify what it really wanted to find.

This is the SEO positioning that is looking for better learning and higher quality content, which is a notable improvement and a benefit for everyone.

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