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In the SEO world, there is some
confusion in what is meant by the term “semantic search”. No wonder. Many
people confuse the definition of “semantic search” with the concept of
structured data (semantic markup). However, these are different things. Some
understand this term solely from the point of view of how it applies to the
field of linguistics, which is connected with the meaning of language and
logic. Let's see what it really means.
What is semantic search?
“Semantic search” is a definition
often used to refer to the efforts that search engines make to understand
queries in natural language. However, it is much broader and also includes the
context in which the user is located at the time a search query is entered.
For example, if a user types the
word "hotels" and the previous query was "Paris", then
there is a chance that he is looking for information about hotels in Paris. Or,
if he previously asked the search a lot of requests on the theme of wildlife,
and enters the query "jaguar", then the probability is high that he
is interested in an animal, and not a car.
In addition, previously, search
engines did not understand the concept of entities, which is that properties
can be associated with people, events, and places. In other words, the Empire
State Building is an object that has height, original architecture,
construction completion date, associated photos, etc. Therefore, if the user
initially performs a search for the query “Eiffel Tower”, and then “What is its
height”, the search engine will show the height of the Eiffel Tower.
Semantic search: what it is and what it is not
Semantic search is to provide the
user with meaningful results based on an understanding of his current intent.
To do this, search engines need to know not only the intention of the user but
also the context of the request. Search engines have made impressive progress
in understanding queries.
Today, search engines are trying
to:
•
Analyze a search query in its entirety, rather
than individual keywords.
•
Take into account who makes the search. Analyze
user’s search history and search patterns to provide personalized results.
•
Take into account how the search itself is done.
Analyze variables such as device type, time of day, and user location.
•
Use advances in natural language processing to
better understand the connections between queries (as in online search), as
well as between different data.
So what does all this mean for SEO?
Currently, traditional SEO strategies
(keywords, quality content, anchor text, and backlinks) are still important.
However, in the new world of semantic search, no single tactic can provide the
desired result. Google’s mission is to provide high quality and reliable search
results. The search engine wants to know that the site and the content that it
shows to the user is relevant and reliable. Therefore, modern SEO is based on
three pillars: credibility, relevance, and trust.
Traditional
SEO strategies, such as keyword research and link building, are still
significant in the semantic search world. However, great content and
user-friendliness today are more important than ever.
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