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This is the official implementation of our paper Personalized Transfer of User Preferences for Cross-domain Recommendation (PTUPCDR), which has been accepted by WSDM2022.
why pytorch and tensorflow use in a package? when i run the code, ModuleNotFoundError: No module named 'tensorflow'
您好,读了您的文章,感觉很有启发,但我还是有一些疑问:
①关于冷启动与热启动。原文说的是数据划分成1:1,具体怎么划分这里并不是很理解,也没有找到相关代码,似乎项目中是直接全部用来测试冷启动的(可能是我没看懂)?
②关于文中table-2冷启动测试结果,请问是基于MF、GMF还是YouTube DNN的呢?
③关于热启动部分,微调和相关测试代码都没有找到,请问方便共享一下吗?
would you like to share these baseline code?
thanks
请问作者大大,data里的train_meta是什么呀
您好,打扰了,请问训练/测试集的比例为什么要划分为三种,因为8:2的表现优于2:8好像是一种不做实验就可以得到的结论,那么请问训练/测试集的用户划分为这三种比例是有什么别的意图或者能够证明什么其他结论嘛?
Traceback (most recent call last):
File "/Users/haiton/Documents/Projects/Autohome/Py_projects/github/WSDM2022-PTUPCDR/entry.py", line 55, in
Run(config).main()
File "/Users/haiton/Documents/Projects/Autohome/Py_projects/github/WSDM2022-PTUPCDR/run.py", line 242, in main
self.TgtOnly(model, data_tgt, data_test, criterion, optimizer_tgt)
File "/Users/haiton/Documents/Projects/Autohome/Py_projects/github/WSDM2022-PTUPCDR/run.py", line 206, in TgtOnly
self.train(data_tgt, model, criterion, optimizer, i, stage='train_tgt')
File "/Users/haiton/Documents/Projects/Autohome/Py_projects/github/WSDM2022-PTUPCDR/run.py", line 191, in train
pred = model(X, stage)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "/Users/haiton/Documents/Projects/Autohome/Py_projects/github/WSDM2022-PTUPCDR/models.py", line 170, in forward
x = self.tgt_model.forward(x)
File "/Users/haiton/Documents/Projects/Autohome/Py_projects/github/WSDM2022-PTUPCDR/models.py", line 60, in forward
emb = self.embedding.forward(x)
File "/Users/haiton/Documents/Projects/Autohome/Py_projects/github/WSDM2022-PTUPCDR/models.py", line 13, in forward
uid_emb = self.uid_embedding(x[:, 0].unsqueeze(1))
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/torch/nn/modules/sparse.py", line 147, in forward
self.norm_type, self.scale_grad_by_freq, self.sparse)
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/torch/nn/functional.py", line 1913, in embedding
return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)
IndexError: index out of range in self
请问有遇到过这个问题吗
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