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Latent Semantic Indexing / Semantic Index definition

Latent Semantic Indexing / Semantic Index (© Profit_image /

Latent Semantic Indexing / Semantic Index (© Profit_image /

Latent semantic indexing is a technique that is used by Internet marketers and language researchers in order to determine what sort of keyword phrases should appear within a document about a specific subject; often used to determine if a piece of content is actually about that subject. If you have been reading articles on search engine optimization or have been involved in that process somehow as a writer of content or Internet marketer, then you have probably heard the term ‘LSI keyword’ at some point. Most people have heard of the term, although not many know what it stands for, and even fewer understand the process of latent semantic indexing.

A very simple definition of latent semantic indexing as it relates to Internet marketing, sometimes called latent semantic analysis, is as follows: the scientific method of analyzing a piece of content to determine what it is about. For those who want a deeper, more accurate explanation, LSA is a language processing technique that analyzes the relationships between pieces of content and terms that they contain in order to produce keyword phrases that will allow a search engine to quickly know what the content is about based upon those LSI keywords.

The Process of Latent Semantic Analysis

The process of latent semantic analysis assumes that words that are similar in meaning are going to occur in similar pieces of text. There is a complicated matrix showing the word counts that should be present per paragraph and complex mathematic formulas are used to determine the similarity and dissimilarity of words.

Search engines use this information to retrieve information from text very quickly. These latent semantic indexing techniques are used to help determine what a piece of content is about and how it compares with other pieces of content that are on the same topic. However, latent semantic indexing is used for much more than the process of search engine optimization.

LSI Applications

  • Comparing documents in order to classify them or for data clustering
  • Finding documents that are similar but are written in different languages
  • Determining the relationship between terms
  • Information retrieval such as in the case of search engine optimization
  • Expand the ability of machines to learn and improve text mining techniques

How Latent Semantic Indexing is used in Internet Marketing

The way that latent semantic indexing is used in Internet marketing is simply by identifying keywords and keyword phrases that may be used to tell a search engine what a document is about. You have a list of terms that you know need to be included with the piece of content in order to tell a search engine that that content is about a specific topic. Previously, keyword density of a particular keyword phrase was used as the main factor in determining what content was about. However, latent semantic indexing is a much more complex process and allows for high-quality search results when it is used to index content on the web.

How to Find LSI Keywords

There are number of methods out there for finding LSI keywords. Latent semantic analysis is a complicated process to complete on your own, but there are plenty of tools out there that will help you find LSI keywords for the purposes of search engine optimization. How it works is that you type in seed keywords that will then generate LSI keywords that you can include in your content. These consist of longtail keywords that will allow you to demonstrate to the search engines what your piece of content is about.

A Demonstration of LSI Keywords

Let’s take a look at a demonstration of one of these tools in action and the LSI keywords that are derived from the seed keyword. In this case, we will go with the keyword ‘car parts’.

Car Parts

  • autozone
  • autotrader
  • advance auto parts
  • barber shops near me
  • car parts used
  • auto parts online
  • auto salvage yards near me
  • auto body panels
  • car parts wholesale
  • a1 auto parts
  • aftermarket car parts
  • aftermarket truck parts
  • car parts names
  • advance auto parts discount code
  • aftermarket auto body parts
  • car parts discount
  • auto body parts near me
  • auto parts warehouse coupon
  • car parts finder
  • aftermarket truck bumpers
  • auto parts warehouse location
  • aftermarket autoparts
  • aftermarket car performance parts
  • body parts pictures
  • auto parts warehouse review

As you can see, not all of these keywords are going to work in your content. For example, barbershops have nothing to do with auto parts. In addition, if you are selling auto parts, you do not want to include the brand names of some of the major auto parts chains such as the ones that are listed here, because they may be your competitors. These tools are definitely not perfect, and you may find some that give you better results than others.

OpenPr-Tip: However, choosing the right LSI keywords from this article will allow you to have a much better chance of telling search engines what an article is about than if you were to simply use the outdated methods of optimizing for a particular keyword phrase with specific densities. These can still be somewhat effective, but LSI keywords are definitely a better option if they are used correctly.

Some of the Benefits of LSI Keywords

  • LSI solves two major problems when it comes to standard keyword queries: multiple words that have almost the same meaning and words that are the same spelling; but have completely different meanings. Both of these have been major issues for search engines.
  • LSI keywords can also be used to automatically categorize documents such as in the case of computer programs categorizing content on the web like search engines.
  • Dynamic clustering that is based on the concept of the document or content can also be completed using LSI keywords. Documents that are conceptually similar to each other can be grouped together without using example documents as a base.
  • Because it is based upon math and not upon specific words, the process of latent semantic analysis can be used for any language, even checking documents that are in different languages using the same algorithm.
  • LSI is not restricted to words either. Latent semantic analysis can also process any random character strings. Anything that can be expressed as text can be analyzed using LSI. In fact, this process is been used to classify genes and has advanced the field of genetics.