Lemmatization is removing the suffix of the word and making it to the base word. Lemmatization is also one of the normalization technique like Stemming in NLP. There are libraries like WordNetlemmatizer in the NLTK package of NLP.
The main difference in lemmatization is the base word should have a meaning. For example: If we do lemmatization for words like ‘Intelligence’, ‘intelligent’, ‘intelligently’, the root will be ‘intelligent’. If we do stemming for the same words, we will get ‘intelligen’.
Lemmatization takes more time compared with stemming. We use lemmatization when the meaning of words is important for analysis. Example: In Question answering application.
You can know more about lemmatization with practical knowledge from this video:
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