In language, the definition of semantics is related to linguistic meaning. So in terms of search, a semantic search engine is doing a study of meaning, focusing on the meanings of search terms being entered. Essentially, semantic search works by drawing links between words and phrases; it’s able to interpret digital content in a more “human” way. When that’s achieved, it can offer the searcher more personalized and accurate search results.
Let’s say you’re getting married and you do a voice search on the English phrase in the lexicon of a bride to be: “dream wedding dress”. A semantics-driven search engine would understand that by “dream”, when it’s linked to “wedding dress”, you mean the synonym “ideal”.
By contrast, a traditional search engine might be confused by the word “dream” and offer a less accurate set of items on the search engine results page (SERP). What does it mean if you dream about wearing a wedding dress? A semantic search engine would probably present as search results wedding-dress styles that it “thinks” would look dreamy on you (maybe retailers’ currently popular styles).
For the past decade or so, search engine technology has relied strictly on keywords themselves in order to interpret the meaning of content. The art and science of getting a web crawler to take notice of your web content’s keywords and thereby highly rank your article in search results is called search engine optimization (SEO).
Optimizing content for the Web has been necessary because search engine technology has not been advanced enough to decipher the meaning of human-generated content as intended. Semantic search is a big leap forward because it supplies more of a focus on searcher intent, contextual meaning from a linguistic standpoint, and a sophisticated understanding of the relationships between words.
Digital marketers might not want to throw out their SEO strategy, keyword research, or lists of ranking SEO terms just yet, but if search engine technology advances enough, in theory, the “intelligence” of semantic search will substantively change how we produce content for the Web, and traditional keywords could become irrelevant.
From the various phrases in user searches, the search engine must figure out whether they want to buy something, and if so, what, exactly; or whether they simply want information about it (e.g., what’s the cheapest soap on the market?). A semantic search engine is better equipped to interpret the meaning of a word. It can better understand query intent, and as a result, it can generate search results that are more relevant to the searcher than what a traditional search engine might display.
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