Refining Textual Meaning through Stemming
Explore the process of stemming in NLP to simplify text analysis by converting words to their base forms using the tm package in R. Understand how stemming reduces unique word counts and enhances algorithm efficiency, and learn how to customize stemming for different languages and datasets.
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Stemming in NLP is the process of reducing words to their base or root form. For example, the stem of the words running, runners, and run is run. Stemming is commonly used in NLP to simplify text analysis by treating different forms of a word as a single term. This helps to reduce the number of unique words that need to be analyzed, which can improve the performance of algorithms that rely on text data.
Using stemming in practice
Let’s explore a practical example of implementing stemming with the tm package. ...