NS-CUK Seminar: V.T.Hoang, Review on "Role Equivalence Attention for Label Propagation in Graph Neural Networks", PAKDD 2020

1. 2023. 04. 14
Van Thuy Hoang
Network Science Lab
Dept. of Artificial Intelligence
The Catholic University of Korea
E-mail: hoangvanthuy90@gmail.com

2. 1
• Existing SOTA Graph transformer models
• Pros & cons
• Problems
• Proposed graph transformer model
• Recommendation system paper
• Related work (edited cross-locations)
• Checking and comments whole paper

3. 2
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 enable the model to learn which distant nodes are more relevant, we
propose a novel attention mechanism based on role equivalence, a social
network property that quantifies similarity among nodes based on their
relational context.
 The attention mechanism is used to merge the multiple node
representations learned from the set of high-order-based GCNs.

4. 3
examples
 we are trying to predict the label of a user D
 high-order paths are potentially useful to learn the underlying hierarchical
roles such as advisor-student in a citation network and admin-member
relationships in a University group on Facebook.

5. 4
Structural Equivalence

6. 5
Regular Equivalence

7. 6
Role Equivalence in latent (embedding) space

8. 7
REGNN Architecture
 k th Order GCN Layers for Label Propagation
 A^{k} is obtained by self-multiplying the adjacency matrix A k-times

9. 8
4.2 Role Equivalence Attention Layer
 Concatenation Layer
 Attention Layer
 Final Softmax Layer

10. 9
Experimental Evaluation

11. 10
Experimental Evaluation

12. 11
XXX
 XXX

13. 12
XXX
 XXX