HKUST-KnowComp

DeepRefine enables the systematic refinement of knowledge graphs by identifying and correcting inconsistencies. It utilizes abduction and mutation loops to verify relational triples against evidence, ensuring higher semantic accuracy and structural integrity within complex graph-based datasets.

Data engineers, knowledge graph architects, and researchers focusing on semantic web technologies benefit from DeepRefine. It is designed for professionals managing large-scale relational data who require rigorous validation and iterative improvement of graph structures.

Implementation requires an existing knowledge graph structure and a defined set of evidence sources for validation. Users must possess foundational knowledge in graph theory and logical reasoning to configure the abduction and mutation parameters effectively.