In natural language processing, lemmatization is the process of grouping together the different inflected forms of a word so they can be analyzed as a single item. For example, the word “better” could be analyzed as a form of “good”. This would be useful in situations where you want to compare all the different forms of a word (e.g., good, better, best) to see which one is most common.
Lemmatization is also used to improve search engines because it can help match different forms of a word with the same root meaning. For instance, if someone searches for “dogs”, they might also be looking for information on “dog breeds” or “dog training”. By lemmatizing these words, you can increase the chances that the search engine will find what the user is looking for.
Finally, lemmatization can make text easier to read and understand because it reduces the number of unique words that need to be processed. When you group together similar words, it makes it easier for your brain to recognize patterns and meanings. This can be helpful when you’re reading something dense or technical; lemmatization can make it simpler and quicker to grasp what’s being said.