Post by amirmukaddas on Mar 12, 2024 11:20:43 GMT 2
What I have defined for a long time as SEO Semantics is a set of reflections on the relationship between terms present in documents of the same or different types, on the same website or on others. The studies conducted over time and the ideas I have developed on the fact that Google is able to recognize precise meanings by correlating different queries and apparently distant web documents have been criticized for a long time by colleagues who, to demonstrate its ineffectiveness, have presented American studies (perhaps) a little cumbersome or they have insisted on the idea that the only correct use of the term "semantics" with respect to SEO is to refer to the semantic web , which expresses its essence in the coding of information easily classifiable by search engines thanks to structured data .
Is semantics then just a matter of structuring data? Machine-side semantics can certainly be attributed to the classification of information through codified syntax, however my studies of the last 3 years allow me to claim a different reading of the term semantics applied to SEO, not an alternative, but complementary to the canonical one. I have been talking about unstructured semantics in conferences for a while , referring to a different level of understanding, which I will now try to explain to you. A new way to talk about entities The entity understood in the classical sense is a piece of Denmark Telegram Number Data data structured according to codified schemes. The price of a product, the author of an article, the featured image, are entities that we can transmit as such to Google as structured data . Having taken note of the "data", Google can decide to attribute a rich snippet to the result in SERP, but it can also determine that a document is relevant for various queries, ending up giving it a high ranking.
The surprise is that this may not happen . I have seen hundreds of websites with perfectly structured data, but completely invisible on search engines, or visible, but with snippets completely devoid of any structured evidence. It happens because the structured data gives Google a direction, not a precise order to show results in a certain way. Evidently Google needs other types of signals , perhaps less obvious and sometimes weaker , to grasp the relevance of a document for a query. These signals are overall the already known endogenous and exogenous factors which range from structural optimization to the profile of incoming links, passing through the relevance of contents in general and texts in particular.
Is semantics then just a matter of structuring data? Machine-side semantics can certainly be attributed to the classification of information through codified syntax, however my studies of the last 3 years allow me to claim a different reading of the term semantics applied to SEO, not an alternative, but complementary to the canonical one. I have been talking about unstructured semantics in conferences for a while , referring to a different level of understanding, which I will now try to explain to you. A new way to talk about entities The entity understood in the classical sense is a piece of Denmark Telegram Number Data data structured according to codified schemes. The price of a product, the author of an article, the featured image, are entities that we can transmit as such to Google as structured data . Having taken note of the "data", Google can decide to attribute a rich snippet to the result in SERP, but it can also determine that a document is relevant for various queries, ending up giving it a high ranking.
The surprise is that this may not happen . I have seen hundreds of websites with perfectly structured data, but completely invisible on search engines, or visible, but with snippets completely devoid of any structured evidence. It happens because the structured data gives Google a direction, not a precise order to show results in a certain way. Evidently Google needs other types of signals , perhaps less obvious and sometimes weaker , to grasp the relevance of a document for a query. These signals are overall the already known endogenous and exogenous factors which range from structural optimization to the profile of incoming links, passing through the relevance of contents in general and texts in particular.