Hi, Thanks for your sharing of this paper! About the datasets Tmall, I find the website you provide in your paper and download the datasets. But I find that in the test dataset, there are no given labels for it. Only the training set has labels. So would you mind share the Tmall test dataset with sessions' labels for us? Thanks!

论文公式2 和代码 alpha = torch.matmul(torch.cat([extra_vector.unsqueeze(2).repeat(1, 1, neighbor_vector.shape[2], 1), neighbor_vector, neighbor_weight.unsqueeze(-1)], -1), self.w_1).squeeze(-1) 不一致，感觉论文公式有误？

Hi, Thanks for your sharing of this paper! In your paper, I can't find whether you sort the session based on timestamp in Nowplaying datasets. The preprocess is unclear. Would you mind sharing the preprocessed datasets Nowplaying? Thanks!

Best regards

python build_graph.py时，已经知道diginetica的sample_num设置为12。但是，数据集Tmall和Nowplaying的超参数sample_num没有给出。请问作者可以给出sample_num在数据集Tmall和Nowplaying上进行build_graph时的设置值吗？

reverse the sequence

us_pois = [list(reversed(upois)) + [0] * (max_len - le) if le < max_len else list(reversed(upois[-max_len:])) for upois, le in zip(inputData, len_data)]

Why reverse the sequence? Thank you.

Thanks for sharing this awesome project! In the RecSys work, https://github.com/andrebola/session-rec-effect, the information about dataset 'Tmall' is inconsistent with that in your paper. And you didn't provide a code to prepare the dataset. So I want to know how that inconsistency exists and hopefully you can provide a guidance in README to help evaluate this project on the Tmall dataset. Great thanks in advance!

Excuse me, at present, I plan to add some other information in the data set to the session-based recommendation task to improve the recommendation accuracy (such as timestamp), and plan to cite and compare your GCE-GNN model. According to what you mentioned in the paper, I have downloaded the original data of the data set Tmall from IJCAI-15 competition（https://tianchi.aliyun.com/dataset/dataDetail?dataId=42) The original Tmall data set contains the information I want to use, but I can’t find the data set 'tmall_data.csv' mentioned in your preprocessing file 'process_tmall.py' . Could you please send me the code for preprocessing the raw data, or send me the relevant processed files 'tmall_data.csv' if convenient, thank you very very much !

你好，想问一下，论文里全局图信息传播只发生在session内节点vi和vi的邻居节点之间，论文中的多跳是指什么意思呢？ 就是正常情况下，一个节点想要利用到其二跳节点的信息，首先肯定是要从二跳节点传递到一跳节点，然后下一层卷积再发生二跳到当前节点的传递。可是论文中只写了当前节点和它的1-hop之间的信息传递。

According to your code in utils.py:

    for i in np.arange(len(u_input) - 1):
            u = np.where(node == u_input[i])[0][0]
            u_adj[u][u] = 1
            if u_input[i + 1] == 0:
                break
            v = np.where(node == u_input[i + 1])[0][0]
            if u_adj[u][v] == 2:
                u_adj[v][u] = 4
            else:
                u_adj[v][u] = 3
            if u_adj[v][u] == 3:
                u_adj[u][v] = 4
            else:
                u_adj[u][v] = 2
            u_adj[v][v] = 1

It seems that u_adj[u][v] will never be set as 2. I test the code on Diginetica and u_adj[u][v] = 2 never happens. Is this a bug or can you show us an example for it? What does 2 stand for?

Thank you.

Excuse me. Does the model that get the results recorded in the paper use the validation set for training? Are the hyperparameters obtained on the validation set first, and then the model is retrained on the training set and validation set? I can't seem to get the results in the paper.

Good job！Could I answer a question？Why the n_node is equal items+1 for diginetica, but are equal items for Nowplaying and Tmall? I reference items from the paper GCE-GNN.

Excellent work! I found that you reproduce the FGNN in your paper,because the original FGNN code is incomplete.Could you release your FGNN code?Thank you.