Demand has grown rapidly as technology has advanced, and consumers can now expect much greater accuracy and relevance for results. While traditional keyword-based searches are still relevant, there is artificial intelligence (AI) based technologies that are redefining our imaginations.
The biggest challenge in working with a keyword-based approach is that it is not always accurate when working with unstructured data. You can also check this link right here now to get more information about artificial intelligence.
Nowadays data is growing exponentially and most organizational data is unstructured. This requires a more efficient approach and semantic search is the solution that businesses need today.
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However, the latter includes gathering all the information relevant to a particular topic. Here the traditional approaches often fail. It is based solely on the presence of keywords, which sometimes is not sufficient to extract all relevant information.
Now the question arises: "How has semantic search changed?" Well, let's take a look at the concept and how it works to understand how it differs from the traditional approach.
The word "semantics" means "meaning" and semantic search engines use AI-based algorithms to understand the query concept for each term and to return the most relevant results. In other words, it's about the results that are in the context of the query.
Semantic search engines use advanced cognitive functions to understand the meaning of queries. This opens up new possibilities for the relevance and accuracy of the results.