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What is Latent Semantic Indexing?

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    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.

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    You have most likely heard of Latent Semantic Indexing (LSI).

    The term has been appropriated by some in the SEO industry, including some well-known influencers. They claim that its application is key for organic search success.

    In fact, a search for [latent semantic indexing] on Google reveals well-known sites such as HubSpot claiming that a little LSI will give your SEO a boost and take it to the next level.

    So, what exactly is LSI?

    And is there any actual evidence that LSI can help your SEO performance?

    To answer these questions, let’s explore the origins of LSI and what it does (or rather, doesn’t) mean for SEO in 2018.

    There is a surprising amount of misinformation about this topic out there; this article debunks the theory that using “LSI keywords” will positively impact your SEO and suggest some more effective strategies you can apply instead.

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    LSI short for 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.LSI is an attempt to overcome this problem by looking at patterns of word allocation across the whole of the web.

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    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.

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    Latent semantic indexing, sometimes referred to as latent semantic analysis, is a mathematical method developed in the late 1980s to improve the accuracy of information retrieval. It uses a technique called singular value decomposition to scan unstructured data within documents and identify relationships between the concepts contained therein.

    In essence, it finds the hidden (latent) relationships between words (semantics) in order to improve information understanding (indexing).

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    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.

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    LSI would allow a search engine to understand synonyms, it follows logically that using synonyms throughout a document could, in fact, help a search engine to understand your content. LSI will give your SEO a boost and take it to the next level.

    Note: White Hat SEO Service is a proven work method to bring the site up on google and another major search engine

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