What Are Natural Language Processing (NLP) And Text Mining?

The role of artificial intelligence is crucial in today’s world. Almost every smart gadget that we see around has a component of artificial intelligence deeply incorporated in it. 

Artificial intelligence is not an easy subject to understand, and even more complex it is to implement. Artificial intelligence has several components to it. Machine learning is also one of it that comes under the domain of artificial intelligence. 

Natural Language Processing (NLP) and text mining are two elements that when bundled to develop an AI-powered application, can work wonders for the business. This article provides a glimpse to create a better understanding of the Text Mining vs NLP. 

Introduction To NLP (Natural Language Processing)

Natural Language Processing has been into existence for more than 50 years now. The process involves automated manipulation of speech or text, collectively known as natural language, by the use of the software. The increasing adoption of computers is one of the major factors behind the increasing interest in natural language processing. 

Natural language processing is basically a component of linguistics study. It is a blend of artificial intelligence, computer science, and linguistics. The whole concept revolves around studying human-computer interactions.

However, there are various challenges associated with it. Natural-language generation and understanding, along with speech recognition, are few of them. 

A Peek Into History

Natural language processing was first heard in 1950. An experiment conducted in 1954 that involved the translation of texts written in Russian. The progress was slow; however, it is lavishly bloomed by the year 1960. SHRDLU became a quality natural language processing system that was introduced in 1960. 

The market worth of Natural Language Processing was recorded at USD 10.2 billion in 2019; however, the experts predict it to touch the USD 26.4 billion figure by the end of the year 2024 making it a profitable business venture. 

To have a better knowledge about the sector, let us have a look at its application first.  

Applications Of Natural Language Processing (NLP)

Knowing about the applications of the technology will help gain a closer insight into it. 

• Language Translator

There are times when people are stuck in a situation because of the lack of ability to interpret the language that changes across borders. This is the time when the role of machine learning solution comes into play. Machine translation is the process that involves retrieval and translation of the text into other languages. 

Earlier the process revolved around a dictionary- or rule-based system. However, with time, the process has evolved, providing accurate information. 

• Social Media Monitoring

Social Media Platforms are increasing in demand to accommodate the increasing number of people willing to share their thoughts about something personal or commercial. Natural Language Processing has a vital role in social media monitoring. 

It is helpful in analyzing and observing public opinion over a product or services. Companies are actively using these services in their systems to keep an eye on the public response about their products and services, eventually helping in strategizing and improvising it. 

• Chatbots 

Enriched customer experience is the key to success for every business. It not only helps keep the quality in check but also helps in addressing customers’ grievances. Manual interaction can be time-consuming. This is when the chatbots come to the rescue. 

Using chatbots can elevate the user experience by solving basic and repetitive user queries. Chatbots have improvised itself and the business a lot during these years. Along with grievance redressal, they also aid in proving product and services suggestions. 

Text Mining

Text mining, also known as text analytics, is an artificial intelligence technology that is composed of natural language processing for processing the unorganized texts from databases or documents into a normalized and organized format. 

The unorganized or unstructured text is complex to process, making it suitable for analytics. Text mining aims to aid the knowledge-based institutions by providing clear insights into the data and information generated from numerous sources.

Applications Of Text Mining

Knowing about the applications of the technology will help gain a closer insight into it.  

• Risk Management

A limiting risk analysis mechanism can bear a negative impact on any sector. Advanced Risk Management Systems based on text mining can be immensely useful for mitigating risk by processing petabytes of documents and analytics, interrelating them, and eventually displaying the collated output.  

• Cybercrime Prevention

The increasing digitization leaves many gateways for attackers to breach into any stable system. Many industries deal with critical information that needs to be safeguarded at any cost. 

With the help of text mining intelligence, public or private enterprises, law enforcement agencies, financial institutions and many others are using it to keep their security in check. 

•  Customer Care

Along with NLP, text mining is extensively used in establishing a reliable customer care network. Text analytics software helps scale-out the information received by multiple sources providing an opportunity for improving business performance. 

Final words

Machine learning solutions are the ideal software that automates a major part of your business that is responsible for determining the success of it. 

Incorporating these advanced technologies into your business operations can be helpful in getting an edge over the competitors, making it a lucrative investment.