Codes for CIKM'21 paper 'Self-Supervised Graph Co-Training for Session-based Recommendation'.

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Deep Learning COTREC
Overview

COTREC

Codes for CIKM'21 paper 'Self-Supervised Graph Co-Training for Session-based Recommendation'.

Requirements: Python 3.7, Pytorch 1.6.0

Best Hyperparameter:

  • Tmall: beta=0.01, alpha=0.005, eps=0.2
  • RetailRocket: beta=0.01, alpha=0.005, eps=0.2
  • Diginetica: beta=0.001, alpha=0.005, eps=0.5

Datasets are available at Dropbox: https://www.dropbox.com/sh/j12um64gsig5wqk/AAD4Vov6hUGwbLoVxh3wASg_a?dl=0 The datasets are already preprocessed and encoded by pickle.

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Comments
  • 关于计算Model文件中np.sum(final_cpu, 0)的报错

    关于计算Model文件中np.sum(final_cpu, 0)的报错

    在运行过程中，ItemConv类的forward函数中，在最后计算item_embeddings = np.sum(final, 0)/(self.layers+1)时，报错TypeError: can‘t convert CUDA tensor to numpy. Use Tensor.cpu() to copy the tensor to host memory first。 想知道怎么改这个错，感谢！

    opened by Andy20178 3
  • Normalization and w_k

    Normalization and w_k

    Hi, thank you very much for your work!

    Do you have any insights why you need the normalization and the w_k factor in computing the final session representations and scores? E.g.:

    sess_emb_i = self.w_k * F.normalize(sess_emb_i, dim=-1, p=2)
item_embeddings_i = F.normalize(item_embeddings_i, dim=-1, p=2)

    Thanks in advance!

    opened by pintonos 1
  • 关于测试集进行shuffle这件小事

    关于测试集进行shuffle这件小事

    作者您好！想请问一下在测试集上进行shuffle的想法是什么？ 对于session recommendation，由于进行了数据增强，[1,2,3,4,5]会拆分成[1,2,3]->[4],[1,2,3,4]->[5]这样的序列，在测试集上建立全局图时若不shuffle会导致建立的图易受较长序列的影响（[1,2,3]->[4],[1,2,3,4]->[5]在同一个batch中，即会在同一张大图中），然而测试集上loss不反传，对模型及实验结果似乎并无影响，此处是否不需进行shuffle。 十分期待您的回复。

    opened by anunverse 1
  • 关于data mask生成的一个疑问

    关于data mask生成的一个疑问

    https://github.com/xiaxin1998/COTREC/blob/c80c4d1f37cc2e0495b1588eb063481a882f8ad5/util.py?_pjax=%23js-repo-pjax-container%2C%20div%5Bitemtype%3D%22http%3A%2F%2Fschema.org%2FSoftwareSourceCode%22%5D%20main%2C%20%5Bdata-pjax-container%5D#L16

    这里data mask没理解错的话应该是要生成邻接矩阵吧，这里sess[i]第一次出现的时候，如果sess[i+1] == sess[i]，比如都是项目k，那么邻接矩阵里k到k不应该再加1变为2吗，按这里的话就忽略了一次变成1；这儿应该是个小bug？ （举例：一个session 1 -> 2 ->2 ->5，假如2是第一次出现，那么字典里2->2的次数按理说是2，但是按代码就是1）

    opened by Zachary-ZS 1
Owner
Xin Xia
PhD Candidate in The University of Queensland
Xin Xia
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