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Recent Trends in Programming languages Review Article

A Comprehensive Study of Natural Language Processing Systems Using Modern Programming Languages: Techniques, Architectures, Experimental Evaluation, and Applications

  1. Sangeeta Singh Department of Computer Science Engineering, Madhav University

Abstract

Natural Language Processing is a key field of study within artificial intelligence that focuses on enabling machines to understand and work with human language. This is because there is much digital text data everywhere. Natural Language Processing is what this study is about. It looks at new ways of doing Natural Language Processing. The old ways are like machine learning and the new ways are like learning. This study compares how well different models work. Natural Language Processing is an important area of artificial intelligence that aims to help computers interpret, analyze, and interact with human language effectively. The study uses known datasets like IMDB reviews and Twitter sentiment data to see how well these models work. First the data has to be prepared. Then the important features have to be found. After that the model has to be trained. Finally the model has to be tested to see how well it works. The study uses measures like accuracy and precision to see how well the models work. The findings indicate that the proposed models outperform the previous ones, mainly because they are more effective at capturing the context and underlying meaning within the text. The old models are simple and work fast. They cannot handle complex text. To make these models work Object-Oriented Programming is very important. It helps to organize the system in an simple way. The code is organized using classes and objects as its fundamental building blocks. This makes it easy to manage parts of the system like data and models. This way of doing things makes the code easy to read and use again. It also makes it easy to add things to the system. The study also talks about the challenges of Natural Language Processing. These challenges are things like needing a lot of computer power and needing a lot of data. With these challenges Natural Language Processing is still a very powerful tool. It can be used in areas like healthcare and education. This study helps us understand how to use Natural Language Processing models and how to make them better, in the future. Natural Language Processing is still. It will be used in many new ways.

Keywords

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