NLTK provides various tools and techniques for text processing, including tokenization, stemming, lemmatization, and part-of-speech tagging. These techniques help in breaking down the text into manageable pieces and identifying the structure and meaning of the text.
Tokenization Tokenization is the process of splitting text into individual tokens, such as words or sentences. This is a fundamental step in text processing as it allows for the analysis of text at a granular level.
Stemming and Lemmatization Stemming reduces words to their base or root form, while lemmatization reduces words to their dictionary form. Both techniques are used to normalize text data, making it easier to analyze.
Part-of-Speech Tagging This technique involves labeling each word in a sentence with its corresponding part of speech, such as noun, verb, or adjective. This helps in understanding the syntactic structure of the text.
