NLP stands for “natural language processing,” which is a term for the technology that lets computers understand how people talk. NLP is what makes it possible for computers to read, edit, and summarize writing. It also makes natural language generation (NLG) possible, which is when computers make up their own “speech.” In other words, NLP is the technology that lets Siri understand what you want, and NLG means that Siri can answer in a way that sounds normal.

Examples of how NLP is used

Some of the most well-known ways that NLP is used are in smart digital helpers like Alexa and Siri. Some examples from the past are predictive text and email spam blockers.

One of my favourites is the popular grammar tool Grammarly, which checks your Word papers, emails, and social media posts for spelling and grammar. (You can get a Grammarly plug-in for Microsoft Office, an app for Chrome, and a Grammarly keyboard for your mobile devices.) The AI-based system was taught by looking at examples of good and bad language, punctuation, and spelling. However, it is always changing and learning. For example, when a Grammarly user ignores a tip, the system learns from that so that it can make better suggestions in the future.

How come NLP is such a big deal?

NLP is an important trend in technology because so much knowledge in the world is in the form of natural human language. Think about all the emails, WhatsApp messages, Twitter updates, news articles, books, spoken talks, and so on that contain information. NLP makes it possible for robots to unlock all of this information and figure out what it means.

In the past, it was very hard for machines to figure out what words meant. Human language is messy, hard to understand, and not well organised. This is very different from the highly organised data that robots are used to processing. AI has changed everything. With the help of AI technologies like machine learning and the rise of “big data,” computers are learning how to process text and figure out what it means.

Businesses can use natural language processing in four easy ways

Analysis of Sentiment

NLP is used in sentiment analysis to figure out how customers feel and what they think by reading their comments, reviews, and social media posts. Businesses can learn how customers feel about their goods or services by looking at the tone of these messages. This knowledge can be used to make things better for customers and to help make new products.


Chatbots are computer programmes that talk to people in a way that seems normal by using NLP. They can be used to automate customer service, answer frequently asked questions, and help customers find their way around goods or services. Chatbots can make customers happier and make it easier for people who work in customer service to do their jobs.

Classification of Text

Text classification uses NLP to automatically put text data into groups that have already been set up. This can help you organise a lot of unorganised data, like comments from customers, posts on social media, and so on. Businesses can use text classification to find trends, keep an eye on competitors, and make choices based on data.

Recognition of Named Entities

Named Entity Recognition (NER) uses natural language processing (NLP) to find and sort named things in unstructured text data, such as people, organisations, and places. NER can be used to look at news stories, posts on social media, and customer comments. Businesses can use NER to keep an eye on mentions of their brand or products, find the people who have the most impact, and keep track of trends in their industry.

In conclusion, Natural Language Processing is a powerful tool that can help businesses get useful information from data that is not organised in a certain way. By using NLP, businesses can improve the customer experience, automate customer service, and make choices that are based on data.

Read More: 8 Reasons Why Businesses Should Use Big Data 

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