Table 4 Comparison of link prediction experimental results of different models.

From: Information flow optimization for adaptive neighbor selection graph embedding

Model

Amazon

DBLP

Retailrocket

ROA

PRA

F1

ROA

PRA

F1

ROA

PRA

F1

R-GCN

0.811

0.820

0.783

0.589

0.592

0.566

0.775

0.748

0.695

MAGNN

0.958

0.949

0.915

0.602

0.699

0.684

0.847

0.847

0.872

HPN

0.949

0.949

0.904

0.692

0.710

0.687

0.796

0.805

0.733

PMNE-n

0.956

0.945

0.893

0.672

0.679

0.663

0.605

0.544

0.689

PMNE-r

0.884

0.890

0.796

0.637

0.640

0.629

0.531

0.503

0.613

PMNE-c

0.934

0.934

0.868

0.622

0.625

0.609

0.567

0.521

0.672

MNE

0.941

0.943

0.912

0.657

0.660

0.635

0.635

0.574

0.632

GATNE

0.963

0.948

0.914

0.659

0.662

0.643

0.502

0.627

0.523

DMGI

0.905

0.878

0.847

0.610

0.615

0.601

0.555

0.502

0.651

FAME

0.959

0.951

0.900

0.742

0.750

0.733

0.646

0.634

0.636

HGTN

0.960

0.950

0.897

0.787

0.832

0.775

0.836

0.854

0.778

SR-RSC

-

-

-

0.719

0.718

0.651

-

-

-

Ours

0.973

0.965

0.965

0.899

0.924

0.899

0.903

0.965

0.904