What Is Semantic Search?

What Is Semantic Search
Source: Seobility

Date First Published: 29th January 2023

Topic: Web Design & Development

Subtopic: SEO

Article Type: Computer Terms & Definitions

Difficulty: Medium

Difficulty Level: 6/10

Learn more about what semantic search is in this article.

Semantic search refers to a search engine's ability to understand the meaning behind a search query and display more relevant results even when searchers didn't accurately or completely construct their queries. For example, when searching for something like 'Mexican restaurants near me', it indicates a local search and Google will show results for Mexican restaurants near the searcher's location even though the search query does not contain the names of those restaurants.

Semantic search goes beyond literal search terms and focuses on the meaning behind a search query. This means that Google and other search engines do not need an exact match keyword to display relevant results. Another example of a semantic search is when misspelling keywords. Google can still display the correct results even if users misspell keywords. Google will recognise the misspelling, convert it to the right word, and display something like 'Showing results for (correct spelling of the keyword)' with another option below to only search for the misspelt keyword.

Semantic search is different from lexical search. Lexical search takes a literal approach to search queries by displaying results that match the query words or variations without understanding the meaning behind a search query. Semantic search aims to improve search relevance and accuracy by understanding the search intent and the contextual meaning of terms.

Google uses semantic search for the following purposes:

  • Getting a better understanding of the user's search intent.
  • Understanding websites and pages in terms of topics rather than keywords.
  • Integrating Google technologies where semantic search has a role, such as Knowledge Graph, Hummingbird, and RankBrain.
  • Identifying and disqualifying low-quality content.
  • Constructing answers to questions.
  • Connecting all possible meanings with search queries when the search intent is unclear.

The main reason why semantic search is important is that it allows search engines to display results relevant to searcher's queries without them strictly relying on keywords themselves in order to interpret the meaning of content. Without semantic search, keywords would have to match the search results displayed, which would make it harder for accurate and relevant results to be displayed if the search intent is unclear.

Another reason why semantic search is important is because of the complexity of the language. A lot of words have multiple meanings, so in order to display relevant results, search engines must be able to understand the contextual meaning of terms. An example of this is the word 'table'. A search engine must be able to differentiate between 'table' as a piece of furniture and a mathematical table. Without semantic analysis, this would not be possible.

After the release of Google’s Hummingbird algorithm update in 2013, a new concept came around, which was semantic search. The main focus of this algorithm update was on natural language and context instead of simply scanning content and looking for keyword matches. Hummingbird uses natural language processing to ensure that "pages matching the meaning do better, rather than pages matching just a few words."

With voice search, a feature that allows users to search using their voice instead of typing, the search is mostly carried out with whole sentences or longer search phrases. In order to display relevant results, Google must have access to semantic understanding.


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