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. LSI considers documents that have many words in common to be semantically close, and ones with few words in common to be semantically distant. This simple method correlates surprisingly well with how a human being, looking at content, might classify a document collection. Although the LSI algorithm doesn?t understand anything about what the words mean, the patterns it notices can make it seem astonishingly intelligent.

By placing additional weight on related words in content LSI has a net effect of lowering the value of pages which only match the specific term and do not back it up with related terms.