I hope the following link will help you to some extent... http://en.wikipedia.org/wiki/Latent_semantic_indexing Good luck.
LSI means that the search engine attempts to associate definite terms with concepts when indexing web pages. It is the detection procedure for finding related terms and also phrases. LSI is mathematical equations that will double words into a matrix for analysis that will sketch out semantically related terms.
LSI stand for Latent Semantic Indexing. Search Engine compares with other targeted keywords for your websites content. If it finds the same niche, or words of similar meaning, then consider relevant in the ground. The whole process is called latent semantic.
Latent Semantic Indexing (LSI) is an indexing and retrieval method that uses a mathematical technique called Singular value decomposition (SVD) to identify patterns in the relationships between the terms and concepts contained in an unstructured collection of text. LSI is based on the principle that words that are used in the same contexts tend to have similar meanings. A key feature of LSI is its ability to extract the conceptual content of a body of text by establishing associations between those terms that occur in similar contexts.LSI is also an application of correspondence analysis, a multivariate statistical technique developed by Jean-Paul Benzécri in the early 1970s, to a contingency table built from word counts in documents.
It is an indexing and retrieval method that uses a mathematical technique called Singular Value Decomposition (SVD) to identify patterns in the relationships between the terms and concepts contained in an unstructured collection of text
Latent Semantic Analysis is a mathematical method that tries to bring out latent relationships within a collection of documents.LSI is the discovery process for finding related terms and phrases. LSI is a maequation that will fold words into a matrix for analysis that will draw out semantically related terms.
[TABLE="width: 800, align: center"] [TR] [/TR] [TR] [TD]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. [/TD] [/TR] [/TABLE]
Search Engine compares with other targeted keywords for your sites content. If it finds the same niche, or words of similar meaning, then think about relevant in the ground. The whole technique is called latent semantic.
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Latent Semantic Indexing (LSI) is an indexing and retrieval method that uses a mathematical technique called Singular Value Decomposition to identify patterns in the relationships between the terms and concepts contained in an unstructured collection of text.