Website analysts spend their days looking for ways to improve a site’s ranking in the list of results that pop up when someone types certain words into an online search engine. Focus on this has created an entire marketing industry that revolves around search engine optimization and tools to increase a site’s chances of being viewed. One strategy that many have not heard of focuses on semantic similarity and semantic distance to promote content based on the words themselves.
Natural language processing
Natural language processing is a tool that search engines use to help find content that matches a specific search. An AI identifies certain words in a section of text that it deems particularly important — more important than the rest of the text. These words are often nouns or pronouns, like names, businesses, numbers, and locations, and the AI picks them out to determine how a webpage should rank with related search terms. A good content writer can take these words and integrate them as relevant SEO keywords, producing a higher rank overall for a website.
Scoring term frequency
In every document, those specific words, called entities, can be matched with certain search words. However, not all-important terms in a document identically match someone’s search. The AI’s score is based on how often a word or term appears in the text. The more it appears, the higher it is ranked in terms of importance. However, if the same word or phrase appears across many texts online, its ranking may get lowered because its popularity indicates it is simply a general term (and is therefore not as important). Balancing these two factors is key in getting the most out of your document terms.
Scoring semantic similarity
“Semantic” refers to the meaning of words. When ranking similarities between words, natural language processing considers how two words may fall in the same category when compared to words that do not relate to them at all. This process can be helpful for finding websites that are relevant but may not contain the exact words in a user’s search.
Reducing semantic distance
Semantic distance is how far apart two words appear in natural language processing. By using words that relate to each other and so fall into the same categories, a writer can produce content that is more likely to be picked up by search engines looking for similar words. That said, beyond simply identifying content topics, with semantic similarity there is a greater chance of sites being organized and ranked based on content. This can make the rankings more convoluted, which is why including words that are similar to search terms can rank your site higher in regard to both organization and topic.
Find more ways to reduce semantic distance in your content
Reducing semantic distance can be a challenge when you do not fully understand how words and terms play into search engine rankings. To learn how to identify and establish words that rank well, contact us for a general guide. We can help you create stronger content that improves your site’s rankings.
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