Knowledge Tagging

Knowledge tagging automatically assigns relevant concepts or keywords to text, such as questions in educational applications. Recent research heavily focuses on leveraging large language models (LLMs) to improve the accuracy and efficiency of this process, particularly for complex domains like mathematics, surpassing the performance of earlier methods based on semantic similarity calculations or LSTM-CRF architectures. This automated tagging significantly aids in tasks like personalized learning, question recommendation, and content organization, streamlining the development of intelligent educational systems and potentially improving learning outcomes.