HIGHLIGHTS
- who: August and collaborators from the Beihang University, China have published the paper: Network representation learning based on social similarities, in the Journal: (JOURNAL)
- what: To address the above challenges, the authors propose a network representation learning method based on the social similarity of nodes. Next, the authors design the representation learning model based on k-truss, which includes three steps: Step 1: Structural Identity Extraction. The authors design a neighborhood sampling strategy based on node similarity that allows the authors to maximize the capture of sequences of nodes with similar structures. The authors first . . .
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