Latent semantic indexing was introduced in an attempt to improve the service offered by Google and other search engines to those using their services.

Keyword density has been the main part of search engine optimization for many years, easily understood by beginners in website design and article writing. The two major factors influencing search engine placement were the use of keywords and in-links (back links).

When Google introduced Adsense, however, it soon became apparent to entrepreneurs that there was a lot of money to be made by generating web-pages specifically designed to display Adsense ads. Thousands of dollars could be made daily by generating thousands of pages, using template-based page generation software specifically designed for the purpose. Content duplication was rife and the websites themselves were of little or no use to the visitor who was presented with nothing more than Adsense adverts.

One of the reasons, perhaps the main one, for the introduction of latent semantic indexing was to overcome this problem, and to ensure that websites were providing a useful service to those using Google’s search engine, though Google is not the only search engine using the algorithm.

Since the introduction of latent semantic indexing, many sites have been de-listed by Google as being of little use to the visitor, and for using duplicate content. A change of keyword was frequently the only difference between pages. Many internet marketers found their income slashed to almost zero overnight, and this change can often be traced back to the time that latent semantic indexing was introduced.

Latent semantic indexing was initially used in Adsense to enable adverts targeted to the theme of a webpage to appear on the page. The algorithm checks the wording on the page and determines the theme of the page. It was only later that Google applied the algorithms to search engine placement, and it is used by search engines other than Google. It involves analysis of words used in natural language, the synonyms and closely related words used when discussing the general theme of a page. It complements, rather than replaces, keyword analysis.

Since it is based on a mathematical set of rules, or algorithm, it is not perfect and can lead to results which are justifiable mathematically, but have no meaning in natural language. Google purchased a company, Applied Semantics, to develop it early in 2003.

So what is latent semantic indexing? How does it work in layman’s terms?

Let’s look at the three words separately:

LATENT.

The word ‘latent’ means something which is present, but not obviously visible. For example, the latent heat of vaporization, or the heat required to vaporize water, is present in clouds, and is only released when it rains. This is why it seems to get warmer during thunderstorms. In terms of latent semantic indexing, it means that a word such as ‘lock’, can be present in a text, and its meaning is hidden until some other factor reveals it. ‘Lock’ can mean, among other things, a piece of hair, a security device or a means of conveying a barge between different heights in a canal. It is only the rest of the text which makes its meaning clear.

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