作者：禅与计算机程序设计艺术
1.简介
Text classification is one of the most important tasks in Natural Language Processing (NLP) that involves categorizing documents into predefined classes or categories. With advances in natural language understanding and deep learning technologies, text classification has become a popular research area for various applications such as spam filtering, sentiment analysis, document summarization, topic modeling, etc. In this article, we will explore the state-of-the-art approaches to text classification using modern techniques such as machine learning algorithms like convolutional neural networks, recurrent neural networks, long short term memory (LSTM), and self-attention mechanism. We also focus on key challenges and open problems related to text classification and provide insights from real-world applications.
In order to keep things simple, we assume readers have some knowledge of basic concepts in NLP such as lexicon,