Lemmatization and stemming for the SEO

One of the essential tasks of sophisticated search engines such as Google is to analyze the texts they find on the Internet and fully understand their content. To do this job efficiently, search engines need to combine the "related" words. This work is called lemmatization.

Lemmatization vs stemming

The lemmatization is the lexical analysis of a text in oder to track the actual words belonging to the same family. Words belonging to the same family are reduced to a single entity called « lemma » or « canonical form ».

Thus, lemmatization is the process of bringing together different forms of unique words.

The lemmatization brings together the different forms a word can take : the plural, the verb in the infinitive, the verb at all times, the noun….

The stemming is the semantic analysis of words in order to identify and bring together different forms of the same word around a root (called « stemme » or « stem »).

The root of a word (or the stemme) is identified by removing the prefix or suffix of a word.

An important difference between the lemmatization and the stemming : a lemme is a real word of the language analyzed, in contrast to the root that is usually not a real word (because it’s based on semantic proximity)

Here is an example of lemmatization and stemming :

Lemme Word
to be be
are
will be
was
Root Word
search searching
let’s search
researchers
researchers

Note that, in certain cases, the root of a word is a real word. For example : the words « frontal » and « front » are derived from the root « front » which is also a real word.

The lemmatization applied to SEO

When it comes to SEO optimization, we will look at the lemma (lemmatization) because it is real words that can be searched for in search engines.

The lemmatization for search engines

When a search engine crawls your web page, it searches for words with the same root and groups them to identify the main topic of your page.

The search engine therefore tries to identify and extract the words with the same lemma in a given text.

It will thus be able to bring all these variants around a main lemma.

Example :

Analyzing our http://www.yakaferci.com/mot-cle/ page, here's what lemmatization could give for the word « Analyze »

Main Lemme captured Word variants detected
Analyze to analyze
analyze
analysis

Through lemmatization, the robots will consider here "analyze" as the main keyword but will also take into account other variants in evaluating the keyword density of the crawled page.

The lemmatization thus captures more accurately the overall content of a page.

The lemmatization applied to content optimization

When developing your keyword strategy and writing your content, you should do the opposite job of a search engine.

You must first identify the main key word and then search for all its possible variations. Then you will place these words in strategic areas of your web pages.

The lemmatization used for SEO means increasing the density of your target keyword using a maximum variation of the latter using prefixes and suffixes. Thus, you enrich your content being less repetitive on a specific word.

Thanks to all the possible variations, the lemmatization also increases the number of different queries through which users could end up on your website.

As each word has a root and inflected forms, it is necessary to identify them for an advanced SEO optimization of the keywords of your pages.

The lemmatization can also be useful for assessing the quality of the backlinks to your site as it allows to vary the text of the backlink while optimizing the target keyword.

Lemmatization tool for SEO optimization

Yakaferci enhanced its keyword density analytical tool by integrating lemmatization in order to allow you to analyze the content of your pages accurately.


Check your Keyword Stemming strategy with Page Analyzer Tool:
ANALYZE


Here is an example :

The report on keyword density integrating lemmatization presents:

  • The main keyword that matches the lemma of the word family analyzed
  • Variants of the main word (lemma) detected in the analyzed page (with their number of occurrences in brackets)
  • The weight of the word (the lemma) calculated based on the occurrence and the position on the page (weight).
  • The number of occurrences shows the number of times all the words with the same lemma are repeated on the page.
  • Positions shows the location of the keywords in the HTML tags of the analyzed page
  • Action: allows us to see the words chosen for the HTML code of the page.