[example] add GGCM #6899
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[example] add GGCM #6899
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Co-authored-by: Hongzhi (Steve), Chen <chenhongzhi.nkcs@gmail.com>
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Description
We add the implementation of GGCM method from the paper From Cluster Assumption to Graph Convolution: Graph-based Semi-Supervised Learning Revisited. GGCM is a very practical unsupervised method, for the advantage of preserving graph structure without the need of learning any parameters.
Table 1: Node classification accuracy.
For comparison, we use DGL's build-in datasets and codes. As shown above, GGCM outperforms another classical "no-learning" method SGC by a large margin.
We are very happy to further improve the code for this great project, and will continue to contribute actively!
Author: Sinuo Xu (undergraduate, @sjtu) advised by Dr. Zheng Wang@SJTU.
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Please feel free to remove inapplicable items for your PR.
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