Semantics and Semantic Search

Semantics is a term from the science of meaning or linguistics. The word comes from the Greek and translated means “doctrine of word meanings”. This means that it deals with the understanding of signs, i.e. words, phrases or symbols. The key point consists of the relationships of signs and their meanings, and there are three basic forms of semantics:

  1. Semiotics (signs and symbols)
  2. semiasisology (word meaning) and onomasiology (object theory)
  3. Linguistics (linguistic signs)

Linguistics and thus the understanding of languages is the relevant area for search engine optimization. This is due to the fact that every user behaves individually on the internet and searches for things in his or her own unique way. Since there are many words that often have the same meaning, search engines rely on semantics to always display the most relevant results in the SERPs.

Semantic search: What is it actually?

Semantic search thus analyzes and focuses on the meaning of the search query. It is no longer a matter of pure keywords, but of the interrelationships of the words with each other. Keyword-based search engines only deliver results that match the corresponding keywords. Semantic search engines, on the other hand, look at the contextual connection of the search query. This helps to display more accurate and relevant search results. Semantics is thus supposed to mimic the human brain and “understand” the search query.

The difference is therefore relatively simple. While keyword-based search engines always display the pages that contain the most relevant keywords in the top positions, semantic search engines use a so-called algorithm. This algorithm establishes relationships between words, phrases and sentences and develops an understanding of connections. This helps you get more relevant and accurate results. For example, if you ask a semantic search engine a question, it searches specifically for the answer, while a keyword-based search engine searches for the keywords of the question.

There are two influencing factors on semantic searches:

Synonyms, which are words that have the same meaning (e.g. “marry” and “wed”).

Synonyms are words that all have the same meaning. So you can represent what you want to express with many different words or phrases. Marry, for example, is the same as "get hitched," "say yes," or „to wed“.
Synonyms of „get married” – one meaning, many words

Homonyms, i.e. the same words with different meanings or ambiguous words.

Homonyms of „can” – one word, many meanings

Synonyms are always included in semantic searches, while homonyms with inappropriate context are excluded from the search results. To be able to do this, the search engine bot needs background knowledge. This works with the help of machine learning.

Potentials and limitations of semantic searches

The advantages of semantic search are clear:

Of course, semantic search also has its limits. For example, if you enter a fairly generic keyword like “rabbits” into the search bar, you will get a wide variety of results, most of which you probably don’t need. So you’ll find results on the differences between rabbits and hares, various videos and products with and for rabbits.

A Google search for the keyword "rabbit" shows that with such a vague search query many different results appear, most of which probably do not display what you want to know.
Google search for the keyword „rabbit”

You don’t get any information about what you have to consider, for example, if you want to keep a rabbit as a pet. However, the search engine cannot guess that this is exactly what you want to know. Here, the algorithm needs further information that it can interpret. That is why long-tail keywords are better in this case. This way the search engine can interpret more into your search and evaluate correlations better. This way you really get what you want to know.

Therefore, if you enter “rabbits as pets” in the search bar, you will get precise results that answer your question. You could also go into more detail and, for example, search for “Which rabbit can I keep as a pet” or “How do I keep a rabbit properly”. However, this is sometimes not even necessary, as the algorithm can already understand the results relatively well and displays what is most relevant in this context.

A Google search for the long-tail keyword "rabbits as pets", on the other hand, is more detailed. As a result, the results usually answer what you want to know.
Google search for the long-tail keyword “rabbits as a pet”.

Semantic search engines – the search of the future?

Definitely yes! It is clear that semantic searches will definitely continue to shape the search engines of the future. But even now the algorithms of Google, Bing and Co. are already on a good way and work strongly with semantics. Therefore, you should make sure in the SEO area that you not only rely on hard keywords in your content, but also on relevance-increasing, semantic keywords.

What is semantic keyword research?

Semantic keyword research is the targeted analysis of keywords that increase the relevance of your content. Semantic keywords are therefore the keywords that are most associated with your main keyword. They help the algorithm to interpret the content more easily and deliver more precise results to the users. To perform semantic keyword research, it’s best to use a WDF*IDF tool. This will then provide the words that are most frequently contained on comparable landing pages with similar content to yours. If you then incorporate these words into your texts, this increases the relevance of your text and improves the understanding for the search engine. At best, this also has a positive effect on your ranking.


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