Text Classification Task

Text classification, a core natural language processing task, aims to automatically categorize text into predefined categories. Current research emphasizes improving accuracy and efficiency, particularly in low-resource settings and with imbalanced datasets, exploring model architectures like transformers (e.g., BERT), graph neural networks, and support vector machines (SVMs), along with techniques such as data augmentation and active learning. These advancements have significant implications for various applications, including legal text analysis, sentiment analysis, and fraud detection, by enabling more accurate and efficient automated text processing.