I’m trying to reproduce the model in a paper Pre-training on Large-Scale Heterogeneous Graph. Basically, it’s a heterogeneous graph contrastive learning method based on Personalized PageRank. To perform PPNP on heterogeneous, they
obtain personalized PageRank Π^𝑅 for a relation 𝑅 by iteratively updating the following:
I don’t understand the following points：
- What’t the initial state of the
- what’s the dimension of Π^𝑅 and Π^𝑅(-1), in my opinion, it should match the number of nodes of the corresponding A_1 & A_2 type.
- Correspondingly, how can the symmetric (by definition) unix matrix I be added to the asymmetric Π^𝑅 (whose dimension should match the number of nodes of the corresponding A_1 & A_2 type)
I email to the authors but haven’t been replied, so I have to seek help here. It would be great if someone familiar with this model could reply to me. Thanks in advance!