In the recent past search engines have delivered results on a single document analysis level basis, where each document is evaluated in a stand-alone mode.
This method of document in text analysis gave enough room for the SEO industry to spam search results. Latent semantic indexing give the search engines the new indexing technology for document indexing.
Latent semantic indexing not only examines keywords in a single document but takes into account the collection of document for a keyword in text analysis. This semantic model gives the search engine a bird’s eye view on how closely these documents are related. A set of Documents that are semantically close gives the search engine an idea about how relevant a website is for a particular topic or keywords. If you’re searching in a Latent semantic indexing (LSI) indexed database then the search engine looks at similar values it has calculated for every synonwyms word and returns the best matched website that will be the best fit to the query. Because latent semantic indexing does not require exact matching words for ranking result.
Lexical indexing is completely based on Lexical analysis. Lexical analysis is the processing of an input which can be a form of sequence of characters which will be produced as output. A sequence of characters or symbols called as lexical tokens. A lexical analyzer will be divided into two stages. First stage is known as a scanner and second stage is known as an evaluator. The Latent Semantic Indexing is depending on these two states. LSI based search engine optimization is much more complex in comparison to normal search engine optimization. The search engine ranking for a particular website will have to pass several processes in the latent semantic indexing based search engine optimization. This process will contain the occurrence of a keyword in a document and the close relationship with the other words of the document, flavor of your website content.
The process of LSI in fact is a boon to our talented content writers who can focus on giving our clients high quality content with the confidence that it will be ranked high for its relevance and information. The process uses the features of natural language whereby words with similar meaning are considered together and unnecessary noise and information is cut out. While carrying out Latent Semantic Indexing, common words such as articles, (like a, an, and the) conjunctions (such as and, but, if) and prepositions (on, in, at, by, etc) are ignored. So are common verbs such as (is, has, are, have) and adjectives like (big, high, tall). The unnecessary words being eliminated, the document is left with words with some semantic meaning.
For LSI based Search Engine Optimization we go through following process
Categorization of the documents
Contextual Explanation from the lexical similar words
Cross-Lingual Text Analysis
Content Relationship Discovery
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