A list of non-exhaustive relevant topics include:

1. -Models and measures for multiplex  & attributed networks.
   

2. -Foundations of learning and mining in attributed networks
   

3. -Centrality and Ranking in Attributed Networks
   

4. -Community Detection in Attributed Networks
   

5. -Link Prediction in Attributed Networks
   

6. -Simplification/pruning/sampling of Attributed Networks
   

7. -User Behavior Modeling in Attributed Networks
   

8. -Social Influence and Information difusion in Attributed Networks
   

9. -Reputation and Trust in Attributed Networks
   

10. -Embedding and Deep Learning in Attributed Networks
    

11. -Probabilistic and Uncertain Attributed Networks
    

12. -Time-evolving Attributed Networks
    

13. -Hypergraph-based modeling, analysis and learning problems
    

14. -Cross-Domain problems in Attributed Networks
    

15. -Visualization of Attributed Networks
    

16. -Personalization and Recommendation in Attributed Networks
    

17. -Mobility in Attributed Networks
    

18. -Vertex similarity in multiplex and attributed networks
    

19. -Multiplex and attributed networks evolution models
    

20. -Multiplex network and dynamic network mining
    

21. -Ensemble learning for multiplex and attributed network mining
    

22. -Pattern mining in attributed networks