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Locationįrom city size to climate, economics to local leadership, countless concepts can affect search results based on location. They have to know that people searching for elevators likely live in North America, but those looking for information on lifts are probably looking for UK-related articles. Semantic search engines must be prepared for language variation and know how it fits into searches. Variation in language use can be regional, age-specific, industry-specific, or rely on any number of demographics. Even though keywords like disease are very ambiguous in this sentence, the engine is still able to parse your intent, among other remarkable things. If you type “What is it called when you think you have a disease but you don’t?” into a search engine, you will get results for hypochondria. A successful system is already visible in countless Google SERPs. But when a search engine sees the keywords oil and health, it may think that you want to know about how olive oil affects your physical health.Īn effective semantic search will strive to guess your intent. If you start talking about oil and how it affects the health of every nation, your conversation partner can probably assume that you mean crude oil. Marketers are already taking advantage of the importance of context in defining searches by focusing efforts on context marketing, wherein marketers match their target markets with demographics reflected by searches. Search results from a semantic search engine can be refined based on these data and assumptions – as long as the search engine understands them. A search for “Etta James” is likely submitted by someone older since we can harness data that says the height of the artist’s popularity occurred in the 1960s. To recreate context, engine developers rely on data and assumptions.įor example, a search for “virtual reality headset” is most likely submitted by a young person or a tech industry professional, an assumption we can make based on the demographics of searchers. Search queries are no different – we expect a reply from the search engine that fits the context of the thing or idea we search for. There are relevant constraints that help us define a word, phrase, or sentence more narrowly so we can produce a reply that makes sense to our interlocutor. Computers have a harder time than we do nailing these down. These are features of our world that our brain processes instantly and without effort - which means we usually take them for granted. Fortunately, those innumerable processes fit fairly neatly into a few underlying concepts that developers use to create quantifiable semantics. Semantics is born of thousands of minute neuro-processes that work in conjunction to create a final meaning. Specialized database searches and site-search tools also take advantage of semantics to make sure they are operating at their optimal efficiency and customers don’t drop off when they can’t find what they’re looking for. Google is not the only company working on a semantic search engine.
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So how does Google develop ways to emulate the intricacies of language? Most of what happens at Google offices is a closely guarded secret, but we can certainly make educated assumptions based on the state of current semantic search capabilities and how they fit into indexing and organizing the web. Since language is the tool that the everyday web user employs to scour the boundless frontier of sites and pages on the Internet, it only makes sense that Google’s inimitable search algorithm would begin to evolve just as language does. Google’s semantic search attempts to improve on the search formula intended to produce relevant search results for web users by creating rules that define a searcher’s intent and the contextual meaning of search terms.Įvery language harnesses the power of semantics to define, clarify, process, and change the meaning of words or words in combination.