Exploring Traditional Methods And Quantum-Based Approaches In Text Classification: A Comprehensive Study On Natural Language Processing

Abstract

This paper presents a comprehensive study comparing traditional techniques with quantum- based approaches in the realm of natural language processing (NLP) for text classification. We delve into the effectiveness and limitations of both methodologies, analyzing their performance across various datasets and benchmarking criteria. Through empirical evaluations, we highlight the advantages and challenges associated with each approach, providing insights into their applicability and potential for improving text classification tasks. By synthesizing findings from existing literature and experimental results, this study aims to contribute to the ongoing discourse on advancing NLP techniques for enhanced text classification.