Why do we use an LSI keyword


What do LSI and LSO mean?

In the process Latent Semantic Indexing (LSI) websites are indexed according to their subject area and not according to a specific keyword. Search engines try, for example, to find documents or websites that deal with the topic of house building, even if the word house building itself is not explicitly mentioned there. With the help of LSI, the search engines can distinguish between documents that really deal with house building and those that only mention the word house building.

The aim of the LSO (latent semantic optimization) is to improve the ranking by adding many keywords in addition to the keyword semantically related words to the search term are included.

Importance of LSI for search engine optimization

In the early days of Google, indexing was done purely keyword based. This means that the search engine checked the indexed documents to see whether the search term entered by a user appears in them. A website on which the search term did not appear was therefore not displayed in the search results by Google, even if the topic of the page exactly matched the search query.

For this reason, individual landing pages were previously created for semantically very similar terms.

By the Hummingbird Update 2013 however, that has changed. With the algorithm change in the course of this update, Google has the semantic search / semantic indexing moved into focus, although Google has not yet confirmed to use LSI.

But the fact is: The topic relevance of a website has been given a much higher priority since the 2013 update. The semantic reference to the keyword on a landing page is more important than the mere mention of the keyword. Due to the latent semantic indexing, landing pages can also appear in the search results that do not contain the keyword at all, but many terms that are semantically relevant for the keyword - the so-called LSI keywords.

However, this does not mean that optimization to one main and several secondary keywords is superfluous. Google continues to check whether the search term / phrase is included, but at the same time checks the thematically appropriate documents for their semantic proximity to the keyword. In simple words: The better the semantic proximity of the content, the better the ranking of the page.

The reaction of the SEO experts to the latent semantic indexing is therefore the LSO.

What is LSO?

LSO means Latent Semantic Optimization or latent semantic optimization. With this type of optimization, care is taken to ensure that words or phrases are used in the texts that are related to the topic of the document or the website and are also used on other websites in connection with this topic. In order to find the most suitable semantically related words, helpful tools are used.

Other ways to find LSI keywords:

The purpose of this optimization is to achieve a better positioning in the organic search results.

Connection between LSI and WDF * IDF

If you know the core functions of a search engine, it is also easier to create content that is optimized for the search engine. That forms the basis here Vector space model by Gerald Salton, on which most search engines are based. In this model, the WDF * IDF method comes into play. A term is viewed from two perspectives:

  • Frequency with which the term occurs in the document - WDF (Within Document Frequency)
  • Occurrence of the term in all documents - IDF (Inverse Document Frequency)

Both are combined with each other in order to determine the actual meaning or relevance of the term. This weighting gives the term a certain place in the semantic space and all documents get a certain orientation in vector space.

A search result would therefore arise as follows:

The search engine examines the indexed documents with regard to their vector alignment in relation to the search term. The most relevant documents are those that best match the search term from the LSI's point of view.

It is therefore important for SEO to look at the semantic space of the documents that rank well for the search term, because from this it can be deduced how your own text can be optimized.

Additional information:

Don't think in terms of keywords!

Semantic analysis