What is the primary function of stemming in natural language processing?

The primary function of stemming in natural language processing is to reduce words to their root form. This process involves stripping affixes (such as prefixes and suffixes) from words to obtain their base or root forms, which helps in simplifying the analysis of text data. For example, words like "running," "runner," and "ran" may all be reduced to the root word "run." This is particularly useful in tasks such as information retrieval, where matching documents to user queries can be more effective when variations of words are treated as equivalent. By focusing on the root form, stemming helps improve the efficiency and accuracy of text analysis without losing the core meaning behind the variations of the words used.

Other functions, such as categorizing words by their grammatical function or assigning sentiments to text, play different roles in natural language processing and do not specifically pertain to the function of stemming. The conversion of visual data into numerical data is also an unrelated process, more aligned with computer vision.