SGCN-master
代码说明：
利用现有的网络结构信息来训练神经网络，从而得到网络嵌入结果。(The existing network structure information is used to train the neural network, and the result of network embedding is obtained.)
文件列表：
SGCN-master, 0 , 2019-01-20
SGCN-master\LICENSE, 1084 , 2019-01-20
SGCN-master\README.md, 6573 , 2019-01-20
SGCN-master\input, 0 , 2019-01-20
SGCN-master\input\ER_edges.csv, 52246 , 2019-01-20
SGCN-master\input\bitcoin_alpha.csv, 166448 , 2019-01-20
SGCN-master\input\bitcoin_otc.csv, 289142 , 2019-01-20
SGCN-master\logs, 0 , 2019-01-20
SGCN-master\logs\bitcoin_otc_logs.json, 2731 , 2019-01-20
SGCN-master\output, 0 , 2019-01-20
SGCN-master\output\embedding, 0 , 2019-01-20
SGCN-master\output\embedding\bitcoin_otc_sgcn.csv, 7749096 , 2019-01-20
SGCN-master\output\weights, 0 , 2019-01-20
SGCN-master\output\weights\bitcoin_otc_sgcn.csv, 5194 , 2019-01-20
SGCN-master\sgcn.jpg, 450781 , 2019-01-20
SGCN-master\sgcn.pdf, 681425 , 2019-01-20
SGCN-master\sgcn_example.jpg, 613188 , 2019-01-20
SGCN-master\sgcn_run_example.jpg, 674763 , 2019-01-20
SGCN-master\src, 0 , 2019-01-20
SGCN-master\src\main.py, 653 , 2019-01-20
SGCN-master\src\parser.py, 3456 , 2019-01-20
SGCN-master\src\sgcn.py, 12494 , 2019-01-20
SGCN-master\src\signedsageconvolution.py, 5069 , 2019-01-20
SGCN-master\src\utils.py, 4002 , 2019-01-20
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