KG Alignment

Knowledge graph (KG) alignment aims to integrate information from multiple KGs, creating a more comprehensive and complete representation of knowledge. Current research focuses on developing accurate and interpretable alignment models, often employing deep learning architectures like transformers and incorporating active learning strategies to efficiently leverage human expertise. These advancements are crucial for improving the quality and completeness of KGs, impacting various applications such as question answering, knowledge-based reasoning, and data integration across diverse domains. Furthermore, research is extending to address challenges like handling knowledge scarcity and enabling "right to be forgotten" functionalities within these aligned KGs.