PageRank is one of several interesting centrality metrics that could be applied to a graph to influence RAG on structural data, another one is Triangle Centrality which counts triangles around nodes to figure out their centrality based on the concept that triangles close relationships into a strong bond, where open bonds dilute centrality by drawing weight away from the center:
The paper shows high efficiency compared to other centralities like PageRank, however in some research using the GraphBLAS I and my coauthors found that TC was slower on a variety of sparse graphs than our sparse formulation of PR for graphs up to 1.8 billion edges, but that TC appears to scale better as graphs get larger and is likely more efficient in the trillion edge realm.
https://arxiv.org/abs/2105.00110
The paper shows high efficiency compared to other centralities like PageRank, however in some research using the GraphBLAS I and my coauthors found that TC was slower on a variety of sparse graphs than our sparse formulation of PR for graphs up to 1.8 billion edges, but that TC appears to scale better as graphs get larger and is likely more efficient in the trillion edge realm.
https://fossies.org/linux/SuiteSparse/GraphBLAS/Doc/The_Grap...