As many of you already know, the future where the internet is heading is what for years some experts have called the Semantic Web. The concept of the Semantic Web was devised by Tim Berners-Lee, inventor of 3W’s. The World Wide Web Consortium (W3C) has been working for several years to improve, expand and normalize this system, which to explain it briefly, aims to implement artificial intelligence technologies that allow the machines themselves to have the level of understanding necessary to organize the web by themselves. The semantic analysis latency (LSA) it is a language processing technique that began to be used in vector semantics in the early 1990s.
Google robots can today do much more than what they did ten years ago; that is, look at your Meta tags and the content of your website in a simplistic way. Today, search engine spiders have a fantastic ability to detect the apparent keywords of each text and make a quick value judgment on the relevance and quality of the text. The search engines use complex algorithms as the method which we will discuss below.
The semantic latency indexing method adds an essential step to the indexing of search engines, the matching of the keywords that a document contains with synonyms and word families around those keywords. In this way, this method examines collections of words and their relationships, comparing them in turn with other documents that have correlations and are cataloged with authority on the subject. Thus, documents that have many words in common have a similar classification, and those that have few words in common will be semantically distant. The closer the vocabulary breadth of your text approaches with a known list of relevant vocabulary around a topic, the more likely your content is to appear in the first position, as it will be considered more relevant and trustworthy. Therefore, the LSI deals with the breadth of appropriate vocabulary and not just keywords. And of course, keyword density does not play any role.
When positioning a web page in (SEO) search engines, most people often think that the best thing to do is concentrate on one or two keywords per page. The semantic latency indexing method completes this idea, allowing us to develop a broader positioning by using correlations between words. By applying this method, search engines strip unnecessary words such as pronouns, conjunctions, and articles from the analysis of a text. In turn, convert plurals, adverbs, and adjectives to their pure form of the noun and verb.
How To Write An Article Thinking About Semantic Analysis?
Write the term to position on a sheet of paper, right in the middle. Around it, write as many words relevant to that term as you can think of. Once you have this list, start writing your content, trying to include a reasonable number of these related keywords that had occurred to you, but of course, try to write and add your words without appearing that someone without two toes has written the content. As a general rule, in a 600-word article, there should be about 10 or 15 of these relevant keywords. In this text, I have used at least 13 terms that I consider appropriate for the words I want to position and to illustrate the example I have contributed color.