Research on Text Categorization Based on Natural Language Processing and Machine Learning

This article aims to study the process of automatic text classification, with a focus on two key steps: feature extraction and classification processing. By adopting suitable feature extraction methods and classification processing models, the accuracy and efficiency of automatic text classification can be improved. The effectiveness of the proposed methods is verified through experiments and evaluations, and a corresponding result evaluation model is proposed to measure the classification performance. The research findings indicate that selecting appropriate feature extraction methods and classification processing models can enhance the accuracy and effectiveness of text classification. In the conclusion section, the research achievements of this article are summarized, and directions and prospects for future research are pointed out. This study provides a complete process for automatic text classification, which is of great guidance significance for practical applications.