A Brief History Of Latent Semantic Indexing

What Is Latent Semantic Indexing?

What Is Latent Semantic Indexing?

Have you heard the term "Latent Semantic Indexing," or LSI, in connection with internet articles and wondered what it was? Well, technically, Latent Semantic Indexing is a way of writing internet documents with meaningful content that rank highly on internet search engines, such as Google.

Latent Semantic Indexing uses a complex algorithm to run a semantic analysis on a document that determines how to rank it on a search page. The algorithm depends on synonymous keywords to determine how they are semantically related to each other and the article's subject. It actually analyzes how words are used in the writing of the article. The method previous to Latent Semantic Indexing also relied on keywords to determine an article's search engine ranking. The difference is that the previous method did not analyze the keywords for semantic meaning. As a result, before Latent Semantic Indexing came into use, you could click on a link and get an article that read simply, "Dogs, Canine, Cats, Kittens, Puppy, Puppies, Shoes, Walking, Running." You get the idea. The document was simply a list of keywords, related or unrelated, designed to attract any internet traffic to the site.

With Latent Semantic Indexing, the document must make sense or it simply does not get picked up by the search engine. In fact, I hope you haven't noticed this, but the last two paragraphs are full of keywords, called LSI keywords, that are related to the term "Latent Semantic Indexing." The algorithm will go through this article, determine that it is about "Latent Semantic Indexing" and determine by the number of keywords used and how they are used how high to rank this article in the internet search engines. This means that in order to rank high on a search engine, an article must have meaningful content.

Why Latent Semantic Indexing?

I already touched on the main problem that pointed out the need for Latent Semantic Indexing: The internet was becoming populated with useless documents. Users were becoming frustrated by clicking on a website's link and finding nonsense information, or even just links of keywords. Even worse, robot software could embed misleading unrelated keywords into a document, and users were being misdirected to incorrect, even offensive, content.

What had happened was an inadvertent side effect of Google's introduction of AdSense. AdSense originally used the Latent Semantic Indexing algorithm to determine the theme of an article. It would then place ads related to the theme of that article on the webpage. People quickly realized the money-making potential of attracting lots of traffic to their webpages and enticing people to view the Ads. This resulted in huge amounts of meaningless documents posted on internet merely to attract traffic to a specific website just to view ads.

In an effort to combat this, Google started applying the Latent Semantic Indexing algorithm to internet articles with the intent of determining their indexing placement in responding to a query. Now, most search engines use it, and the result is a significant reduction of misdirection and nonsense documents.

by: Justin Beightol

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