Question

Differentiate Stemming and Lemmatization. Explain with an example.​

Answer 1

Answer:

Stemming and Lemmatization are Text Normalization (or sometimes called Word Normalization) techniques in the field of Natural Language Processing that are used to prepare text, words, and documents for further processing. Stemming and Lemmatization have been studied, and algorithms have been developed in Computer Science since the 1960's. In this tutorial you will learn about Stemming and Lemmatization in a practical approach covering the background, some famous algorithms, applications of Stemming and Lemmatization, and how to stem and lemmatize words, sentences and documents using the Python nltk package which is the Natural Language Tool Kit package provided by Python for Natural Language Processing tasks.

Answer 2

Explanation:

Stemming and Lemmatization both generate the root form of the inflected words. The difference is that stem might not be an actual word whereas lemma is an actual language word.Stemming follows an algorithm with steps to perform on the words which makes it faster.