Resource Description Framework Star Graph

RDF Star graphs represent knowledge by allowing statements about statements, creating nested structures that capture complex relationships within knowledge graphs. Current research focuses on developing query languages (like extensions of SPARQL) to efficiently manage and reason over these complex structures, and on creating graph embedding models (such as adaptations of node2vec) to learn meaningful representations for use in machine learning tasks like classification and link prediction. This work is significant because it enables more nuanced representation of knowledge, particularly in domains with intricate relationships and contextual information, leading to improved performance in various data mining and knowledge representation applications.