NLP which stands for Natural Language Processing is one of the most exciting technologies on the market today. Many businesses are interested in how it can help them achieve their goals but don’t know where to start. In this blog, we are going to look at Natural Language Processing and how it is going to impact technology and business.
NLP is a segment of artificial intelligence that assists machines or computers to read, understand and interpret human language just like humans do. Irrespective of whether the language is spoken or written, NLP with help of AI uses the input, analyzes it, and produces some understanding out of it for the machines to process. NLP integrates statistical, machine learning, and deep learning models with computational linguistics—rule-based modeling of human language. These technologies work together to allow computers to interpret human language in the form of text or speech data and ‘understand’ its entire meaning, including the speaker’s or writer’s purpose and mood.
What are some major applications of Natural Language Processing (NLP)?
Every successful organization has a typical data warehouse that stores a blend of a diverse mix of data and information gathered from various sources. The insights obtained from this data have propelled organizations into a new realm of consumer awareness, but restricting analytics to this sort of highly organized format negates the vast bulk of data currently being generated. Unstructured data accounts for 80% of all data produced. It comes from talks with customer service agents, as well as conversations on social networking sites and other locations. Natural language processing (NLP) technology is being used by businesses to extract meaning from the vast amounts of unstructured data available online and in call logs.
Numerous NLP activities assist the machine to understand what it’s absorbing by breaking down human text and speech input. The following are some of these responsibilities:
- Email filtering: One of the most popular applications of Natural Language Processing is email filtering. Email providers can prevent spam-based email content from accessing their mailboxes by evaluating the text of the emails that go through their systems.
- Data extraction: Many vital business choices are steadily migrating away from human monitoring and management. Various business choices in fields such as finance are impacted by news-inspired feelings. Text, infographics, and photos make up the vast part of the news material. Taking these texts, analyzing, and extracting associated information in a manner that can be utilized in decision-making capacities is a significant challenge for Natural Language Processing. For example, headlines of a large merger can have a significant influence on corporate choices and trading algorithms, with potentially millions of dollars in profit consequences.
- Identification of voice: Companies may construct sophisticated voice-driven interfaces for any system using technologies built with the aid of Natural Language Processing. Natural Language Processing (NLP) is being used by businesses to interpret human language and inquiries. Rather than relying on regular human language use patterns to grasp ideas, the company’s platform relies on a specific knowledge graph generated for each application, which does a considerably better job of finding concepts that are significant in the client domain.
- Analysis of emotions: The capacity to extract insights from text and emoticons from social media is a commonly used activity by businesses all over the world. For enterprises in just about any industry, digital media provides an immense potential to acquire the needs, opinions, and intent that consumers communicate on the web and social media. Listening to the customer’s speech necessitates a thorough knowledge of what they’re saying in Natural Language: NLP is the most effective approach to comprehending human language and deciphering the emotion behind it.
NLP for the Future
With the growing volume of text data created every day, natural language processing (NLP) will become increasingly vital in making sense of the data and in many other applications. Today we can observe a digital marketing industry shifting to data-driven marketing. Through social listening, digital marketers and companies may now discover what consumers’ interests, pain issues, and brand impressions are by analyzing enormous amounts of text data on a wide scale.
Customer services are highly supported through chatbots in the banking industry for financial consultants by answering consumer concerns more quickly, correctly, and, most importantly, in a human-like manner. NLP has altered our interactions with computers and will continue to do so in the future. As AI technologies modify and enhance communication technology in the years ahead, they will be the underpinning driver for transformation from data-driven to intelligence-driven initiatives.