What is the difference between tokenization and stemming?
An example of an AI chatbot conversation about tokenization and stemming in NLP.
What is the difference between tokenization and stemming?
Tokenization is the process of breaking text into individual words or phrases, while stemming reduces words to their base or root form.
Can you give me examples of each?
Sure! For tokenization, the sentence 'I love programming.' becomes ['I', 'love', 'programming']. For stemming, 'running' might be reduced to 'run'.
Why is tokenization important in NLP?
Tokenization is crucial because it helps in understanding the structure of the text, making it easier for algorithms to process.
Are there any tools for tokenization and stemming?
Yes, popular libraries like NLTK and SpaCy provide built-in functions for both tokenization and stemming.
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