International Journal of Swarm Intelligence and Evolutionary Computation

Significance of Natural Language Programming

Yinhai Wang^* Department of Civil and Environmental Engineering, University of Washington, Seattle, USA
^*Correspondence: Yinhai Wang, Department of Civil and Environmental Engineering, University of Washington, Seattle, USA, Email:

Received: 06-Dec-2021 Published: 31-Dec-2021

Description

Natural Language Processing (NLP) is an element of AI in the field of linguistics that deals with interpretation and manipulation of human speech or text using software. It enables the computer to understand the natural way of human communication by combining machine learning, deep learning and statistical models.

Language is a system of communication with the help of which we can speak, read and write. For illustration, we suppose, we make opinions, plans and further in natural language; precisely, in words. Still, the big question that confronts us in this AI period is that can we communicate in an analogous manner with computers. In other words, can human beings communicate with computers in their natural language? It’s a challenge for us to develop NLP operations because computers need structured data, but human speech is unshaped and frequently nebulous in nature.

In this sense, we can say that Natural Language Processing (NLP) is the sub-field of Computer Science especially Artificial Intelligence (AI) that’s concerned about enabling computers to understand and process human language. Technically, the main task of NLP would be to program computers for assaying and recycling huge quantum of natural language data.

Natural language processing (NLP) is a subfield of linguistics, computer wisdom, and artificial intelligence concerned with the relations between computers and mortal language, in particular how to program computers to reuse and dissect large quantities of natural language data. The thing is a computer able of understanding the contents of documents, including the contextual nuances of the language within them. The technology can also accurately extract information and perceptivity contained in the documents as well as classifies and organizes the documents themselves.

More recent systems based on machine- learning algorithms have numerous advantages over hand- produced rules. The literacy procedures used during machine literacy automatically concentrate on the most common cases, whereas when writing rules by hand it’s frequently not at all egregious where the trouble should be directed.

Automatic literacy procedures can make use of statistical conclusion algorithms to produce models that are robust to strange input (e.g. containing words or structures that haven’t been seen ahead) and to incorrect input (e.g. with misspelled words or words accidentally neglected). Generally, handling similar input gracefully with handwritten rules, or, more generally, creating systems of handwritten rules that make soft opinions, is extremely delicate, error-prone and time- consuming.

Conclusion

Significance of Natural Language Processing Applications: The biggest benefit of NLP for businesses is the ability of technology to detect, and process massive volumes of text data across the digital world including; social media platforms, online reviews, news reports, and others.

Also, by collecting and analysing business data, NLP is able to offer businesses valuable insights into brand performance. In addition, NLP models can detect any persisting issues and take necessary mitigation measures to improve performance.

With NLP, it’s possible to perform certain tasks like Automated Speech and Automated Text Writing in lower time. Due to the presence of significant data around, why not we use the computers unflagging willingness and capability to run several algorithms to perform tasks in no time. These tasks include other NLP operations like Automatic Summarization and Machine Translation.