To put in a layman’s terms, latent semantic indexing (LSI) is a technique of indexing - analyzing, listing or categorizing certain keywords or phrases in the contents of various websites, books or documents in such a way that they have contextually and conceptually the same or related intent and meaning despite the different words used in them.

The technique used in latent semantic indexing aims at finding the keywords in the text that carry a latent relationship in structure and usage. The idea behind the concept of LSI is to collect data that is conceptually akin in meaning and context to the search queries entered by the searchers in the search engines. The search results may, therefore not share the specific words or phrases entered by the searcher.

For example, if you use the word ‘Saddam Hussein’, the search engine may return articles about the Gulf War, situation in Kuwait or Iran, the elite force of the Iraqi despot, UN sanctions, oil fields in Iraq and much more without even mentioning the search word ‘Saddam Hussein’.

The technique of LSI automates the process of categorizing the documents almost the way the human beings do. The text selected may not have the same words or sentences. The results returned may have lists, free notes, web content or even emails.

Advantages of latent semantic indexing
Sometimes the web searcher is conscious that he is not using the right keywords or phrases due to the lack of knowledge of appropriate vocabulary. He, therefore, uses only approximate words which may not return the desired information if the search process follows the Boolean pattern. Latent semantic index technique facilitates the retrieval of the related conceptual content even if the search queries do not use the ‘correct’ words.

Latent or true information
LSI technique returns information in its true conceptual representation, which is not easily possible through the traditional search approach. It uses synonymy that can bring forth the underlying concept even if the searcher uses different words or phrases. The traditional retrieval process does not always discover the right content on the same topic that uses different vocabulary.

Polysemy
A large number of words have multiple meanings. So, if a searcher uses numerous polysemous words, they may reduce the chances of getting the precise information. LSI helps to weed out the unnecessary words from the data and tries to arrive at the average meaning, which is close to the real meaning of the search queries.

Sifting close and distant words
LSI examines the contents of the different websites or documents and tries to find out which of these contain semantically common words, similar words, closer words or distant words. This is almost working like a human being. Although LSI does not understand the meanings of the words, its algorithm does notice the word patterns and indexes them accordingly. This process proves the astonishing intelligence of the LSI technique.

How should one use latent semantic indexing?

Latent semantic indexing is a very useful tool for search engine optimization of your website or copywriting.  You should, therefore, use the keywords and phrases very carefully. For example, if you are using the keyword or phrase ‘buy jaguar’ you should explain what the word ‘jaguar’ stands for since it is a polysemous word. It may mean a cat, a car or an aircraft. It may also be a brand name of some sanitary product.  Using the word ‘jaguar’ in isolation may confuse the LSI tool. You should, therefore, clarify what your ‘jaguar’ stands for. Otherwise, you will defeat the very purpose of launching your website.

You should also be careful in the use of synonyms so that they convey the meaning that you exactly want to communicate. Synonyms are very helpful in clarifying the meanings of the words. But stuffing keywords for making the site SEO compliant may also defeat the purpose and your site may be blacklisted for spamming.

What happens if one does not use latent semantic indexing?