Node and edge dual-masked self-supervised graph representation
Peng Tang,
Cheng Xie,
Haoran Duan
Abstract:Self-supervised graph representation learning has been widely used in many intelligent applications since labeled information can hardly be found in these data environments. Currently, masking and reconstruction-based (MR-based) methods lead the state-of-the-art records in the self-supervised graph representation field. However, existing MR-based methods did not fully consider both the deep-level node and structure information which might decrease the final performance of the graph representation. To this end,… Show more
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