Can Natural Languages Provide A Stable Enough Environment For Productive Programming?

Programming languages hold a prominent position in the field of information technology as these languages are used to develop a computer program. These languages allow a computer to perform some specific operations. The languages are developed in a specific syntax and are used to develop high level languages.

To make these languages more productive and efficient, the industries are shifting towards using natural languages for creating various IT applications. In the era where every little thing is shifting towards a digital environment, something like programming needs strong processes to develop specific computer programs that work efficiently.

This is the era of big data and the maintenance and manipulation of such a huge amount of data needs specific programming syntax. Natural language programming is one such alternative that can be used to manipulate and process this chunk of data.

Natural language processing (NLP)  refers to a subset of artificial intelligence that paves a way for the computers to analyse and interpret human language in a useful way. The developers can easily perform numerous tasks such as speech recognition, sentiment analysis etc. using natural language processing. Using this programming language, the developers can structure knowledge and perform varied tasks such as relationship extraction, translation, topic segmentation etc. These languages process on some fundamental rules, based on a specific grammar structure which can be used by the people to enhance communication technologies.

Natural language processing is rapidly entering the IT industry and it works via machine learning technology. This technology stores words, sentences , phrases etc. and the machine learning engine process the language based on certain grammatical rules and other attributes. The computer process this data to find various patterns attached to it and create a program. It eliminated the need for hand coding, reducing the burden on developers and allowing them to focus on strategic aspects of the industry.

Apart from developing a specific program, NLP is also used by the job recruiters to sort resumes and attract diverse and high-qualified candidates. NLP is also being used by the industries for spam detection to keep unwanted e-mails out of inbox.

Besides processing data, NLP can also be used to contribute to society and understand society through the use of sentiment analysis. Industries are using this program to process language and facial expressions to detect peoples’ emotional state and understand society in a better way. Through natural language processing, the problematic states can be flagged, enabling the social workers to intervene to understand the complexity and work accordingly.

Natural language processing is contributing in making computers as intelligent as humans as far as understanding the language is concerned. This language works with a definite grammar structure named Syntax which helps in describing the computer language and natural language. It has enabled the non-programmers to obtain information from computer systems through various levels of interaction.

This algorithm also has the ability to dig out insights from the data that is present in any unstructured material such as videos, mails etc. which can be used by the developers to draw information for developing computer programs. These languages are highly used for communicating between people and other programming languages, enhancing interaction between humans and machines.

Programming is a complicated topic that necessitates a high level of skill in order to create error-free computer programs. Natural languages enables swifter development of programs, cutting down on minor errors, which in turn, leads to creating an efficient computer program.

NLP also allows the tracking of popular and trending topics as it works on a hierarchical structure of language that enables better performance, enabling correction and translation. NLP enables breaking down the structure, leading to extraction of relevant information as human language can be a bit ambiguous and difficult for a machine to extract information.

Through sentiment analysis tools, the industries can spot messages and tweet and provide what customers’ requires by breaking down the context in which they appear. Earlier, NLP was used by industries only for classifying feedback as positive and negative but now, natural language processing has entered into diverse units of insformation technology industry.

Natural language processing has also enhanced sophisticated communication through the use of its tools like Botometer, which works by analysing language for effective computer communication.

NLP has transformed the ways IT industries develop programs, eliminating the need to use traditional technologies, thereby increasing efficiency of the process and reducing minor errors. NLP has enhanced the communication of computers with the users, without the need for the users to learn a new language.

NLP works by retrieving related content and choose the required words and setting tones of the sentence. Semantics works by understanding the language of the sentence and predicts how the language is interpreted. It is also used for entity recognition by identifying the entity extracted from a person or an organisation through summarization and keyword tagging. It is also useful for rudimentary translations by translating one human language to another human language. It reduces the time required for such translations by using its advanced tools. It converts the human language into a mass information and stock it into a database.

It also enables monitoring the brand’s performance through the use of semantics, by analysing consumer behaviour. Natural language processing can also be used by a visually impaired person to interact with computers due to its user-friendly interface. It is also used for converting spoken language into text using the deep learning technology.

This language can also be used for math computation, algorithm development and many other engineering graphics. It also enables statistical learning by exploring data, using statistical methods and graphs. The industries use NLP for investigating big data and intense learning analytics.

NLP can be used in various other ways such as creating a chatbot by using a deep learning model. It is used to identify the sentiment behind a string of text using sentiment analysis.

All in all, natural language processing has made the job easier for developers by providing them with various advanced tools and applications. It certainly doesn’t mean that it would take away the jobs of humans. NLP requires human interference to work efficiently and grow in the industry. This programming language has eliminated the loopholes that were earlier present in the IT industry, making their process efficient and effective. It has entered the IT industry with a wide range of advantages, making this industry to grow further.