What is NLP (Natural Language Processing)?

Business Management
What is NLP (Natural Language Processing)

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Think about the last time you searched for something on Google, asked chatbot a question, used voice-to-text option in your mobile phone or translated something online. You would have probably used a simple human language and not any special commands or programming language to do the same. And the technology manages to understand enough your request and provides benefitting responses.

Have you ever wondered what facilitates this? It is the ability of Natural Language Processing or NLP.

As Artificial Intelligence became a part of everyday business activity and personal technology, the role of NLP becomes significant. Behind many tools that people use for searching information, automate support and work with written information, there is NLP.

What is the Meaning of NLP?

Natural Language Processing is a branch of Artificial Intelligence. It helps computers understand and communicate human language. Human communication will rarely be structured. We use abbreviations, slangs, emotions, different sentence structures and even sarcasms. This is where NLP comes into role and bridges the gap to make computers understand and communicate human language. NLP can work with both written and spoken language.

Why is Natural Language Processing Important?

Computers are good at processing structured data, whereas businesses generate huge amount of data every day that appears in an unstructured format including emails, customer reviews, reports, contracts, social media posts, online enquiries and chat messages. Analysing these data manually can a longer time. NLP helps businesses analyse these data more efficiently and this could save a lot of time and effort.
  • When you ask a question, NLP understands and tries to answer the question.
  • When you submit a document, NLP analyses and gives the important information.
  • When a customer feedback is submitted, it says whether the feedback is positive, negative or neutral.
Understanding NLP becomes a necessity in the world where Artificial intelligence and automation are no longer the buzzwords but a daily part of life.

How NLP Works?

To understand how NLP works, think you are saying a sentence to the computer. If the same is said to the human, the human can understand it almost immediately. But it doesn’t work the same with computers. It has to break it down, analyse and then determine the meaning of the sentence. The processes that the NLP systems go through may vary from one to the other. But they involve several general stages.
The stages include,
  • Text collection (Data collection)
  • Processing and cleaning the text data (Data processing)
  • Breaking sentences into smaller parts (Language analysis)
  • Understanding the meaning (Machine Learning)
NLP Workflow
NLP Workflow

What are the Main Techniques in NLP?

Natural Language processing doesn’t just have a single technique, it has multiple methods based on the task it is performing.

Tokenisation:

Tokenisation is the process of breaking down the sentences into smaller parts like the words and phrases. It is to make the process easier and help the system analyse each part better. It is usually the first stage of NLP.

Sentiment Analysis:

It identifies whether a piece of sentence expresses positive, negative or neutral opinion. It is used by businesses to analyse employee feedback, reviews and surveys.

Text Classification:

It is used to segregate texts into pre-defined categories. For an example, a customer support message can be classified into product enquiry, delivery details, complaint or general enquiry.

Name Entity Recognition:

Nama entity recognition is used to identify several information within texts including people’s name, location, organisation, dates and products.

Machine Translation:

Machine translation is used to translate information from one language to another. Modern translating platforms translates not just words but also sentences and contexts proving more natural translations. Businesses operating in multilingual markets can hugely benefit out of this.

Text Summarization:

NLP can give a summarized context out of lengthier documents, articles and reports. This can save a lot of time while businesses deal with lengthy documents.
NLP Techniques
NLP Techniques

What is the Difference Between NLP, NLU and NLG?

NLU and NLG are almost related, but they are not the same. They both fall under the broader area of NLP.
  • NLP – Natural Language Processing – A broader category that helps computers process and work with human language.
  • NLU – Natural Language Understanding – It helps systems understand the meaning, context and the intent.
  • NLG – Natural Language Generation – It helps systems to generate useful responses that are in readable language for human.

What are Some Examples of NLPs?

The term Natural Language Processing may sound like a complicated technical jargon. But the following examples will make it more familiarised to you and they are the ones that people already use regularly.
Examples,
Search Engines: NLP helps the system to interpret what you are searching for.
AI Chatbots: NLP is used to make the system understand the human language and provide appropriate responses.
Language Translation: Translation tools use NLP to interpret the sentence and translate them from one language to another.

What are the Industries that Benefit out of NLP?

NLP has become so important across industries because almost every industry uses language. Whichever industry that uses documents, report, surveys and conversations, NLP has potential usage.

Some of the industries that have NLP application:

Human Resources: NLP helps in data management, document classification, resume shortlisting, HR chatbots and survey analysis.
Marketing: NLP is used to analyse customer comments, campaign feedback and customer behaviour.
Banking and Financial Services: Banking and finance department deals with large amount of documents and conversations. Financial news analysis, complaint classification and document analysis can be done with NLP.
Healthcare: The selective medical and administrative documents can be analysed with NLP. However, healthcare applications require careful and professional oversight.

What are the Benefits of Natural Language Processing?

  • NLP understands the human language better and this makes the use of technology much easier.
  • The sentiment analysis in NLP helps businesses understand the concerns and preferences of the customers.
  • NLP provides answers to the questions though they are asked using a simple language. This improves the access to information.
  • Chatbots and automated responses make businesses answer the queries so fast.

How NLP Supports Modern Businesses?

NLP may sound so technical but the value that it adds to the businesses are straightforward. Businesses use NLP these days not just because they are available. It reduces unnecessary, so that employees may utilize the time and work towards something requires human judgement. This effectively helps for the overall growth of the businesses.

For Malaysian businesses that look for digital transformation, the technology like NLP shows how AI can be used even in ordinary companies rather than other technologies which can be applied only in technology related companies.

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NLP Frequently Asked Questions

Wha is NLP in AI?

NLP is a part of AI that focuses mainly on communication and language. It allows AI to communicate with people using simple human-language instead of computer languages.

Natural Language Understanding (NLU) and Natural Language Generation (NLG) are the two components of NLP.

A customer service Chatbot and voice assistants are the two examples pf NLP.

NLP is used to make the computers understand, analyse and respond to human requests in a human understanding language.