LSI Indexing

[Roseanne Hortense]

What is Latent Semantic Analysis (LSI Indexing)?

 

[Rashi Aggarwal]

LSI keywords or Latent Semantic indexing, is an alternative name given to synonyms and similar words by Google and search engine experts. LSI are synonyms to normal keywords and these words can be used to get higher ranks in Google and other search engines. The synonymous keywords make your blog post sound more natural and that is the thing that Google likes.

 

[josephinek]

LSI is Latent Semantic Indexing.
It is an indexing method that works out which words are relevant to other words.

 

[sonikathakur]

LSI is latent semantic indexing algorithm. It can be helpful in SEO services...

 

[alexbarry]

LSI (Latent Semantic Indexing) is useful to maintain the keyword density and to be safe from keyword stuffing.

 

[min]

Latent semantic analysis (LSA) is a technique in natural language processing, in particular distributional semantics, of analyzing relationships between a set of documents and the terms they contain by producing a set of concepts related to the documents and terms. LSA assumes that words that are close in meaning will occur in similar pieces of text. A matrix containing word counts per paragraph (rows represent unique words and columns represent each paragraph) is constructed from a large piece of text and a mathematical technique called singular value decomposition (SVD) is used to reduce the number of rows while preserving the similarity structure among columns. Words are then compared by taking the cosine of the angle between the two vectors (or the dot product between the normalizations of the two vectors) formed by any two rows. Values close to 1 represent very similar words while values close to 0 represent very dissimilar words.