Text Classification is a type of machine learning task that uses Natural Language Processing (NLP) techniques to automatically assign text content to predefined categories or labels. By analyzing the vocabulary, semantics, and contextual information in text, this technology enables the automatic organization and management of large volumes of unstructured text data, making it one of the foundational tasks in information retrieval, content analysis, and intelligent decision-making systems.

The development of text classification is built on long-term research in fields such as statistical language models, machine learning, and natural language processing. Early methods typically relied on manually designed features (such as bag-of-words models and TF-IDF) combined with classification algorithms to determine text categories, but they had certain limitations in complex semantic understanding and feature representation. In 2014, Yoon Kim, a researcher at New York University, proposed a method for sentence classification using Convolutional Neural Networks (CNN) in the paper Convolutional Neural Networks for Sentence Classification, demonstrating the effectiveness of deep learning models in text representation and classification tasks, and establishing it as one of the important representative research works in the field of deep text classification.

Modern text classification methods typically use pre-trained language models (such as BERT-type models), large language models (LLMs), and deep neural networks to learn semantic representations of text, and to accomplish tasks such as sentiment analysis, topic classification, intent recognition, and spam detection. With the development of large-scale language models, text classification has gradually shifted from methods relying on manual feature engineering to methods based on semantic understanding and contextual modeling, with continuously improving adaptability in complex text scenarios. Currently, this technology is widely applied in fields such as public opinion analysis, search ranking, customer service systems, content moderation, and enterprise knowledge management.