Semantic Annotation

Semantic annotation focuses on enriching data with meaningful labels and relationships, improving machine understanding and enabling more sophisticated data analysis. Current research emphasizes automated annotation methods, leveraging large language models (LLMs) and other deep learning architectures to overcome the limitations of manual annotation, particularly for large datasets. This work is crucial for advancing various fields, including education (knowledge tracing), healthcare (medical image analysis and clinical report summarization), and data science (tabular data interpretation and knowledge graph construction), by improving data quality, accessibility, and interpretability. The development of robust and scalable semantic annotation techniques is driving progress in numerous applications.