What is behind content relevance search?

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It is a major challenge to show users the most relevant results based on only a few words/keywords. This has been solved since the 1980s and 1990s with the help of so-called full-text search. The relevance of a document compared to the entered search query is calculated using mathematical formulas.
One of the most well-known formulas is TF-IDF (often referred to as WDF*IDF in SEO), which compares the frequency of a word/term with the frequency of that word/term in all other documents in a so-called index.

All search engines initially began as pure full-text search lithuania cell phone number list engines and likely used this or similar formulas to best satisfy users' search intent. However, with the ever-increasing number of websites, this formula soon became insufficient to best answer search queries.

Therefore, modern search engines rely on many additional ranking factors and mechanisms, such as related word recognition. They are becoming increasingly better at displaying the most relevant results, matching search intent, at the top of the results page.

At their core, modern search engines, especially Google, are and remain full-text searches across the entire internet. Rankings for specific keywords are only possible with high full-text or content relevance.