Latent Semantic Indexing

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Latent Semantic Indexing – Definition & explanation

Latent Semantic Indexing
Figure: Latent Semantic Indexing - Author: Seobility - License: CC BY-SA 4.0

Latent Semantic Indexing (LSI), also called Latent Semantic Analysis, is a method used to improve information retrieval by identifying relationships between terms used in a document. Latent semantic indexing can be used in natural language processing to improve the understanding that computers have of a piece of content.

In SEO, LSI is used by some to help improve their on-page SEO, helping them find relevant supporting terms to cover on their pages. It can also be used to find relevant content ideas or information that could be added to a page in order to make it more relevant.

Latent Semantic Indexing Screenshot

Screenshot of seobility.net showing an example of various words that are semantically related to the main keywords “SEO”

LSI & Search

In the early days of search, search engines like Google relied solely on keywords in order to judge the relevance of content. This came with a variety of problems, including mass keyword stuffing by website owners in a bid to improve their SERP rankings.

As search algorithms adapted, aspects of natural language processing were introduced to take focus away from exact match keywords and keyword density. It was thought that LSI was a big part of this transition, although it was never confirmed by Google. This caused SEOs to place more focus on related keywords and writing content for visitors instead of search engines.

Its use today

Today, LSI is used as a guideline by some SEOs as opposed to being seen as an actual ranking factor, with many not using it at all. It can be used to uncover related terms that can enhance the topical relevance of a piece of content.

Another use for LSI is to uncover potential gaps within the content of a post. By better understanding what terms are relevant to a page’s main keyword, it’s possible to improve the quality of the content.

LSI keywords

“LSI keywords” is a term used to describe words that are semantically related to the main keyword of a page. These words help add contextual relevance to a piece of content, potentially allowing search engines to better understand what the content is about.

This is especially relevant when the main keyword can have different meanings, or when words within a key phrase have strong differing meanings when used alone.

So-called LSI keywords aren’t the same as synonyms, which are words with the same or nearly the same meaning as the main keyword.

Relevance to SEO

Although LSI was used for optimizing webpages in the past, today, it’s not used as often. However, it can still be used to provide an indication as to how relevant content is, as well as provide information on topics that can help improve the depth of content.

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