Fig 1.
Random walk sampling methodology (in the figure C-R stands for co-reliable authors, C-P stands for co-publication sites and RT stands for relevant titles).
Fig 2.
Fusion embedded modules.
Fig 3.
Example of random sampling.
Fig 4.
RA-HGCN network model.
Fig 5.
Examples of data sets.
Table 1.
Comparison of the methodology of this paper with several classical methods for the three types of indicators.
Table 2.
Comparison of this paper’s method with ten baseline methods on the Aminer dataset for three types of metrics.
Table 3.
Comparison of the effectiveness of this paper’s method with ten baseline methods for disambiguation on the Aminer dataset.
Table 4.
Comparison of ablation experiments.
Table 5.
Comparison of the methods in this paper on three different datasets.
Fig 6.
Comparison of actual and predicted clustering of RHAC in six different names.
The origin of the figure shows the actual clustering effect, and the × sign shows the predicted clustering effect.
Fig 7.
Comparison of time consumed by different clustering algorithms when K value is known and the score.
Fig 8.
Comparison of time consumed by different clustering algorithms when K value is known and the score.
Fig 9.
The effects of the number of attentional heads on the experimental results.
Fig 10.
The effects of the number of attentional heads on the experimental results.