Unsupervised Text Classification

Unsupervised text classification is a technique in the field of natural language processing that aims to automatically categorize large amounts of text data into different categories without manual labeling. This method achieves effective organization and management of text content by mining the underlying structure and patterns within the text data. The goal of unsupervised text classification is to enhance the usability of text data and the efficiency of information retrieval, reducing the cost of human intervention. Its application value is extensive, including but not limited to document clustering, topic discovery, sentiment analysis, etc., providing powerful data insights for enterprises and individuals.