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The world wide web is a fairly new resource to the world when compared to books, manuscripts, and even ancient hieroglyphics. In the primitive times of the internet, hundreds and thousands of websites were available and there was no organized way to find them. Once internet marketing took off, it became nearly impossible to find the websites and information you needed. A gauge of how useful a website is for what you're looking for was needed, or in other words, we needed latent semantic indexing. This is when the need for search engines came along. They make it possible for internet users to search a specific word or words to get relevant results. The technical term for this process is latent semantic indexing. Google was one of the first companies to devise a way for internet users to search a word or phrase and be returned with relevant and organized results. The process this is accomplished by is latent semantic indexing. Google uses a mathematical matrix to return only sites with an adequate amount of keywords and search terms. The first website to be returned will have the highest keywords and therefore be the most relevant to the keywords you searched. LSI allows internet users to more efficiently search the web. There is a lot more to LSI than one might think. The matrix works to only give you results that are going to be useful. This is accomplished by latent semantic indexing by measuring the amount of keywords compared to the length of the article or website text. This matrix ensures that you aren't going to be directed to a website that lists your search term many times but is pages and pages long and isn't going to do you any good. This is a condensed version of what latent semantic indexing does. It is much more complex, but still has become very popular, even outside the professional technology world. Internet marketing companies have harnessed this power as well and uses it to get the attention of potential buyers to their products. How exactly do the latent semantic indexing robots "measure" the keywords in an article? The LSI method gauges how far apart the keywords or search terms are from each other and mathematical calculates its relevance and how high it should be placed on the search results page on Google or another search engine website. Internet marketing uses this to their advantage by placing keywords schematically in their product articles to be found first on a Google search. Google has also created a way to eliminate the websites that are "too" full of keywords and search terms. Most of these are junk advertisements and spam websites. Latent semantic indexing calculates and determines if a website or article has too many keywords to possibly be useful and doesn't allow them to show up on the search results page. Internet marketing companies therefore have to be careful not to put too many keywords into their ad articles. Websites that have a good ratio of keywords as well as an ample amount of related terms to the keywords are will show up higher on the Google search results page. Latent semantic indexing performs analysis of keywords first and then a calculation of pertinent words and phrases along with them is figured out. These related words are words that are often found together and complement each other in an article. For example, a roofing document will have recurring words like shingles, homeowner, contractor and repair. These words would be related terms. 9417a171b03e5d525af32049870a7d01 http://LSIKeyWords.com http://lsikeywords.com/Latent-Semantic-Indexing.html 9417a171b03e5d525af32049870a7d01
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