Search engines like Google and Yahoo have been using Latent Semantic Indexing (LSI) as part of their search results for some time. Google started doing this in 04.

Although LSI is not a new topic for search engine optimization, it is very important for the development of ranking relevance, building long search queues, but now for universal search.

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What is LSI and how does it work?

Latent semantic indexing is a key component of how search engines understand the "context" of website content. LSI is based on a concept called word grouping together and document association based on source data.

In short, search engines basically learn the meaning of a word based on other words around it. This practice is very important in many languages because words often have multiple meanings.

For example: let's look at the word "shoes".

At this point, you really have no idea which shoe I'm referring to.

If the surrounding text is about triathlons, marathons, jogging, or brands like Nike, Brooks, and Saucony, now you know that shoes mean running shoes.

However, if the surrounding text mentions drums, pads, rotors, discs, and metal, or brands like Raybestos and Bendix are represented, you now know that shoes mean brake shoes.
Of course, now you know that a shoe means a horseshoe if the text around it mentions hooves, pasok, lapak, and lapak.

Other related words on this page help search engines understand the "context" of keywords and keep search results relevant. Without these words of clarification, you wouldn't know which shoes appeared in your search query. With these related words, search results are now more relevant.

In addition, these related words help build long lines of search terms. With the development of the right keywords and content, it is not uncommon for several hundred to several thousand keywords to be reached. In fact, many of our clients often only have 25 keywords as part of their SEO campaigns, but 12 months later they have accumulated 500-2,500 keyword combinations and permutations through Google Analytics.

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Now with universal demand, LSI is even more important. The purpose of universal search is to identify and refine search intent. Universal search now combines different types of media as a product of search results.

When looking for a Hawaiian vacation, people expect you to shoot, if not video, on the beaches of Maui. In addition to previewing a particular tour, you'll also want to hear a podcast of that tour.

When you sell big prom dresses, people expect not only the styles from the last years but the styles from this year as well. If you are looking for a prom dress, you may also need matching shoes, handbags, hair accessories, etc.