What is the process that identifies the roots of search words and groups their invariants to aid in text analysis?

Lemmatization is a crucial process in text analysis that involves reducing words to their base or root form, known as their lemma. By identifying the roots of search words, lemmatization enables the grouping of different forms of a word under a single representation. This is particularly useful in natural language processing, as it allows for more accurate analysis of text data by treating variations of the same word as equivalent. For instance, "running," "ran," and "runs" can all be reduced to the lemma "run," aiding in search functionality and improving the accuracy of algorithms that depend on word meaning and context.

Other processes mentioned, such as tokenization, focus on breaking text into individual components (tokens) like words or phrases, without necessarily considering their root forms. Parsing involves analyzing the grammatical structure of sentences, while keyword extraction identifies and selects significant words or phrases but does not perform the same root identification as lemmatization. Thus, lemmatization specifically addresses the need to understand the underlying meaning of variations in words, streamlining the analysis of text data.