In other words, high-confidence course concepts in CCG could propagate their confidence scores to their neighbor nodes that have high semantic relatedness with them, to discover other potential course concepts.
we propose an iterative graph-based algorithm, namely course concept propagation (CCP), which first assigns each vertex of CCG an initial confidence score, and iteratively updates the score for each vertex through propagation.