In the field of “Natural Language Processing” (NLP), the capacity of a computer program to comprehend human language in its spoken and written forms sometimes referred to as “Natural Language,” is defined. In artificial intelligence, it is indeed an element.

Natural language processing (NLP) allows computers to interpret natural language in the same way that people do. Natural language processing, which may be used to either spoken or written language, employs artificial intelligence to accept real-world information, analyze it, then make logical sense of it in a manner that a computer can comprehend.

Automated question answering is carried out via chatbots and virtual assistants, which are meant to interpret natural language and offer an appropriate response through natural language generation. Also known as information extraction, text extraction automatically finds certain information in a text, such as names, corporations, locations, and other elements. This is referred to as named entity recognition in certain circles. Besides keywords from text, you may extract pre-defined information such as product serial numbers and models from a reader as well.

The concept of automatic summarization is very self-explanatory. It provides a concise summary of a book by extracting the most significant elements. Among its primary objectives is to make the process of sifting through large volumes of data, such as scientific articles, news items, or legal paperwork, more straightforward.

Customers’ support tickets, social media postings, survey replies, and other unstructured data are all processed using natural language processing systems, which assist firms manage massive volumes of data. It is also used to automate time-consuming processes, as well as to acquire insights to aid in decision-making and to assist decision-making.