Search Engine Optimization needs constant update about various strategies and techniques invented by search engines. Search engines are rapidly involved in upgrading their search technology with change in time and web technology. Latent semantic indexing is the latest algorithm invented by Google.

Latent semantic indexing allows a search engine to determine what a page is about outside of specifically matching search query text. When Google introduced Ad sense, 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 Ad sense ads. Keyword density, search engine optimization, and reciprocal links have long been essential elements for getting websites ranked high in search engines. Now with the rising numbers of sites content duplication crept in which was in real sense no use to the visitors.

This calls for the introduction of latent semantic indexing. Latent semantic indexing adds an important step to the document indexing process. In addition to recording which keywords a document contains, the method examines the document collection as a whole, to see which other documents contain some of those same words. 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 search engine finds website by finding inbound links, links from other websites to your website, and following these to your site. When in your site the spider will read your code. From the code it will Index all the on and off screen content. When you search an LSI-indexed database, the search engine looks at similarity values it has calculated for every content word, and returns the documents that it thinks best fit the query. Because two documents may be semantically very close even if they do not share a particular keyword, LSI does not require an exact match to return useful results. Where a plain keyword search will fail if there is no exact match, LSI will often return relevant documents that don't contain the keyword at all.

LSI enables result by finding near matches to searches where exact matches aren't found. As it adds weight to related words and removes the duplicate content, chances of spam sites gets reduced. The other advantage of LSI is that it is a mathematical approach, with no insight into the meaning of the documents or words it analyzes. This makes it a powerful, generic technique able to index any cohesive document collection in any language.

This conclude that you  should maintain a reasonable density of the specific keyword being targeted, since that is still the term being used by the searcher, but you must also use related words and terms to define the overall theme of the page.