Natural Language Processing for Text Mining: Leveraging Linguistic Features for Classification

Natural Language Processing, or NLP, is key for digging through and finding important bits in large pools of text. This study looks at how we can use bits of language, like how words are put together and what they mean, to sort text in NLP better. Language is full of complex patterns, and we're diving deep to figure out how to use these to make text sorting smarter. We're looking at things like grammar, meaning, and the setting of words, and using tools that help us spot different parts of language, feelings, and names. These tools help our model catch the fine details that ordinary approaches might miss. We're testing how well these language details do at sorting text by using the latest machine learning tools. Our work points out the tough parts of working with different kinds of language and offers new ways to handle these for better text sorting. As info spreads across many areas, our study helps make NLP models stronger. They can handle the complex world of human speech better, pushing forward the work in text sorting and categorizing.