Lemmatization - Nomidl

Day 4: Stemming and Lemmatization

IntroductionNatural Language Processing (NLP) plays a critical role in understanding and processing human language. This blog discusses stemming and lemmatization, essential text normalization techniques in NLP. What is NLP and Its Components?NLP is an AI-based method of interacting with systems using natural language. It involves several steps: tokenization, lemmatization, POS tagging, named entity recognition, and…

Step-by-Step Process of Implementing Stemming and Lemmatization in Python?

Install the Natural Language Toolkit (NLTK) library. This library provides a range of tools for natural language processing, including stemming and lemmatization algorithms. You can install it using pip install nltk. Import the necessary functions from the NLTK library. For example, to use the Porter stemmer, you would use the following import statement: from nltk.stem.porter…

Stemming vs Lemmatization Difference: Explained in Detail

Introduction When dealing with large amount of text data, it becomes essential to preprocess and analyze the text effectively. Stemming and lemmatization are text processing techniques that help reduce words to their base forms, helps you in better analysis and understanding. Stemming Stemming is a technique that aims to reduce words to their root form,…