Latent Semantic Indexing-Seo Resources Page

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The closest search engines have come to actual applications of this technology so far is know as "Associative Indexing" and it is put in effect under Stemming, or the indexing of words on the basis of their uninflected roots (plurals, adverbs, and adjectival forms are reduced to simple noun and verb forms before indexing).Latent Semantic Analysis (LSA) is a technique in natural language processing, in particular in vectorial semantics, invented in 1990 [1] by Scott Deerwester, Susan Dumais, George Furnas, Thomas Landauer, and Richard Harshman. In the context of its application to information retrieval, it is sometimes called Latent Semantic Indexing (LSI).

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Latent Semantic Indexing adds an important step to the document indexing process. In addition to recording which keywords a document contains, the method examines document collections as a whole, to see which others do contain some of those same words. LSI considers documents that have many words in common to be semantically close, and ones that have few words in common to be semantically distant. This method correlates surprisingly well with how a human being looking at content, classifies multiple documents.