Named Entity Recognition in R: Extracting People, Places, and Things from Text (Paperback) (ISBN-13: 9798252903729)

In today's data-driven world, vast amounts of valuable information are hidden inside unstructured text news articles, social media posts, customer reviews, research papers, and more. But how do you turn this raw text into meaningful insights?

Named Entity Recognition (NER) is the key.

This practical and comprehensive guide teaches you how to extract and analyze real-world entities such as people, locations, organizations, and more using the power of R programming. Whether you are a data scientist, analyst, researcher, or student, this book provides a clear pathway from foundational concepts to advanced applications in text analytics.

Designed with both beginners and experienced users in mind, this book walks you through the complete NER workflow from understanding text data to building fully functional entity recognition projects in R.

The fundamentals of Named Entity Recognition and natural language processing
How to prepare and preprocess text data for accurate entity extraction
Rule-based and machine learning approaches to NER in R
How to use powerful tools like spacyr, udpipe, and tidy text workflows
Techniques for extracting entities such as people, places, organizations, and dates
How to apply pretrained models and fine-tune them for real-world use
Advanced methods including deep learning and transformer-based models
Visualization and interpretation of extracted entities for actionable insights
How to build, evaluate, and deploy a complete NER project in R

This book goes beyond theory by focusing on practical, real-world applications. Each chapter is structured to help you build skills progressively, ensuring you can confidently apply NER techniques to your own datasets.

You will not only learn how to extract entities but also why certain methods work, and when to use them.

• Data analysts and data scientists working with text data

• R programmers looking to expand into natural language processing

• Researchers in computational linguistics and text mining

• Students and professionals interested in NLP and AI applications

• Anyone who wants to transform unstructured text into structured insights

By the end of this book, you will have the skills to build powerful NER pipelines in R, enabling you to extract meaningful information from text and support smarter, data-driven decisions.

If you're ready to unlock the hidden value in text data, this book is your complete guide to Named Entity Recognition in R.