Hi,
what is latent semantic indexing?
Regards,
Jeya vinoth
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.
Latent Semantic Analysis (LSA), also known as Latent Semantic Indexing (LSI) literally means analyzing dоcuments to find the underlying meaning or concepts of those dоcuments. If each word only meant one concept, and each concept was only described by one word, then LSA would be easy since there is a simple mapping from words to concepts.
Latent semantic indexing it is an algorithm used by search engines to determine what a page is about outside of specifically matching search query text. The LSI algorithm doesn't actually understand the meanings of words on the page but it can spot patterns of related words. LSI will may return relevant results that don't contain the keyword at all, but those pages with related words.
LSI keywords stand for (Latent Semantic Indexing) those keywords which semantically related to your primary keywords, google doesn't accept repeated keywords more than 5 to 6 % of your main keywords otherwise it will consider keyword stuffing and it will decrease your ranking in search engine, you can use its similar keywords of your main keywords in your content.
Latent Semantic Analysis, as the name suggests is the analysis of latent i.e. hidden semantics in a corpora of text. A collection of dоcuments can be represented as a huge term-dоcument matrix and various things such as how close two dоcuments are, how close a dоcument is to a user issued query, etc. can be inferred by cosine similarity, Jaccard Index, etc