Heterogeneous graph neural network for attribute completion

Heterogeneous graphs consist of multiple types of nodes and edges, and contain comprehensive information and rich semantics, which can properly model real-world complex systems. However, the attribute values of nodes are often incomplete with many missing attributes, as the cost of collecting node attributes is prohibitively expensive or even impossible (.ttribute ompletion framework for terogeneous .