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How Latent Semantic Indexing is achieved

Latent semantic indexing is a type of technology that works to understand what a page is about. Since most website owners do some type of keyword spamming, search engines had to invent better ways of realizing the relevance of the webpage. Latent Semantic Indexing is merely one process within search engines’ complex ranking algorithm but it can affect your search engine listings considerably. Latent semantic indexing is a search engine algorithm that performs keyword-based analysis to index the web pages. Search Engines realized that they needed a better way for the bots to ascertain the true theme of a webpage and that's what Latent Semantic Indexing is all about. The idea of LSI is to identify the meaning of the information, which words, sentences and documents can be mapped among other website pages. Latent Semantic Indexing is going to change the search engine game; you will need to change your SEO efforts to pay off big time. 

 

LSI is introduced to improve the performance of text filtering; LSI is a statistical technique for extracting and representing the similarities of words by analysing large collections of text. Latent semantic indexing is a process by which you can determine the subject matter of a web page without relying on specific keywords. 

 

In order to understand how Latent Semantic Indexing is achieved, it is important to know some basic high school math, particularly Cartesian coordinates. 

 

Typically, when a search query is sent a term-document matrix is created. The pages that have been previously processed send back results that contain the correct semantic meanings. 

 

All formatting from the pages including capitalization, punctuation and extraneous makeup are removed. 

 

Also, the conjunctions, common verbs, pronouns and prepositions are removed. Lastly, the common endings are removed and what you have left are the stem words. 

 

In order to plot the position of the web page, you need to think of the page in terms of a three -dimensional shape. 

 

Using three words instead of three lines, you are able to achieve this image. The position of every page that contains these three words is known as a term space. 

 

Each page forms a vector in the space and the vectors direction and magnitude determine how many times the three words appear in the structure. 

 

With three words, it is easy to imagine what the resulting form may look like, and the resulting query would turn up a good number of correct searches. 

 

Instead, if every word and every page were represented, then the dimensions would be endless. But it is not practical to assume seeing every web page in existence. This is just not possible, nor is it probable. 

 

Typically, a term-document matrix is created from pages that have been pre-processed. This is so that only the words, which have the semantic meaning, remain. All formatting of the pages include capitalization, punctuation. 

 

The search engine ranking for a particular website will have to pass several processes in the latent semantic indexing based search engine optimization.