Thanks to the RankBrain software developed using artificial intelligence, the machines running Google's search algorithm began to guess what users actually wanted to search for with the phrases they typed while listing complex search results. Thus, thanks to the semantic algorithm change made in the background, Google began to understand the chickpeas without saying a word. Google, which guessed not only the phrases that users searched for but also the results they wanted to reach, enabled access to content in a shorter time.
Search engines are now changing users’ searches according to the correct form of the query to present results. They first return results for words that are easier to process. No matter how you malaysia phone number example search, Google can change it according to the correct form of the query. Want an example to make it clearer? Okay; for example, if you have searched for flights before and typed “buy a ticket” into your search engine, you will see results for flights, not bus or train. But when you want to associate these queries with people, places and events, you need to take a different approach. For example, when you search for “Bosphorus Bridge” in Istanbul, you can get various information about this structure; however, to directly learn the length of this structure, you need to search for “how long is the Bosphorus Bridge”.
If you have decided to make your website the most efficient for the user, you need to be able to think like him. In the world of semantics, unfortunately, just identifying keywords is not enough. You need to work in more detail. During the search, your engine helps you complete your statement by adding frequently searched keywords while you are still entering the words. You can take a look at these suggestions while determining your keywords, so you can learn which words other users search for the most.
Semantic search means providing meaningful results to the query made by the user. with the intentions of people while searching. To do this, search engines try to understand not only the user's search intent but also the context of the query. Instead of keywords, they take into account the entire search query. They provide personalized results by paying attention to who is performing the search, the user's search history and search patterns. They take into account how the search was performed, such as device types, search time and location. Results are presented to the user by understanding the relationship between queries and data by taking into account the capacity to process natural language.