yuanyuansiyuan / icde-2020-smgcn Goto Github PK
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License: MIT License
hello, in the process of following your SMGCN, I tried to reproduce the code in the repository, and referred to the experimental settings and results in the paper, but found that the NDCG indicator in the results is significantly different from the experimental results in the paper, I want to consult whether the NDCG calculation method you use in the paper is different from the code, if it is different, I hope you can explain the specific calculation process, thank you very much for your patience, and look forward to receiving your reply
当我根据目前的train.txt和test.txt中的样本数据进行重新随机划分训练集和测试集后,训练时会显示ERROR: loss is nan.
Hello, author. After conducting experiments using the optimal parameters mentioned in your paper and the code provided by you, I have been unable to achieve the results you mentioned. The best recall@5-10-20 achieved was 0.19529, 0.30444, 0.44125, respectively, and the corresponding precision@5-10-20 was 0.27290, 0.21536, 0.15851, and ndcg@5-10-20 was 0.37745, 0.45431, 0.55460. However, the GCMC model achieved a better recall@5-10-20 of 0.20790, 0.32693, 0.47173, precision@5-10-20 of 0.29062, 0.23090, 0.16946, and ndcg@5-10-20 of 0.39072, 0.46893, 0.57103 using the optimal parameters mentioned in your paper. Do you have any idea what could have gone wrong and why this happened?
2022年2月,环境应该用tf1.15,已经下载不到tf1.8了,实测1.15可以运行。
Feb. 2022, you may apply tensorflow1.15 instead of tensorflow1.8 as mentioned in readme. tensorflow1.8 is no longer available. I did test and 1.15 is runnable.
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