Dimensions Of Latent Semantic Indexing
Latent semantic indexing is commonly used to match web
search queries to documents in retrieval applications.
LSI has improved the retrieval applications.
It has improved retrieval performance for some, but
not all, collections when compared to traditional
vector space retrieval or VSR.
Latent semantic indexing allows a search engine to
determine what a page is about by searching for one or
more keywords that are selected by the user.
LSI adds an important step to the document index
process. Latent semantic indexing records keywords
that a document contains as well as examines the
document collection as a whole.
By placing importance on related words, or words in
similar positions, LSA has a net effect of making the
value of pages lower so they only match specific
terms.
Latent semantic indexing has fewer dimensions than the
original space and is a method for dimensionality
reduction.
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