Comments (6)
Thank you for your interest in our paper.
The label information in the raw data indicates whether the user is a repeat buyer, which is not related to our task and has not been used in our work. For the Tmall dataset used in our work, the label of each session is the last item in the session.
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Thanks four your response!
But when I preprocess the datasets, the statistics are different with your papers.
For Tmall datasets, I use the train_format2.csv and test_format2.csv in the website.
For the preprocess, I firstly get all the sessions, and leave the first 120000 sessions.
For the 120000 sessions, I filter sessions whose lengths are 1 and larger than 40. Then I filter the items who appear less than 5 times. And then split the sessions.
But I still have different datasets with yours showed in your paper, Table1.
So would you mind share the preprocessed datasets for us or tell me my mistakes in the preprocess?
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If you share the preprocessed datasets for us, we'll appreciate. It is more convenient for us to make comparisons with your model.
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UPDATE: in the train_format2.csv, there are only 4995 items, but in your paper, there should be 40728 items.
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Thank you for your interest.
We have updated the preprocessed Tmall datasets. You can also download the raw Tmall data from the dropbox link in the paper Evaluation of Session-based Recommendation Algorithms.
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Thank you very much!!!!!!!!!!
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Related Issues (20)
- Could you release the FGNN code?
- 最优结果 HOT 1
- Tmall数据集及处理 HOT 2
- Original csv of Tmall and Nowplaying HOT 1
- 信息传递和信息汇聚问题 HOT 1
- Tmall数据集问题 HOT 1
- Validation
- Data_preprocess HOT 1
- 关于数据集 HOT 1
- build_graph时超参数sample_num在另外两个数据集Tmall和Nowplaying的设置值 HOT 2
- n_node about the datasets HOT 1
- nowplaying.csvs数据在哪里找
- dataset problem
- indicator problem HOT 2
- Question about lack of source code license
- About validation
- Where to concatenate content features of node? Should it be before attention network?
- About preprocessing on Nowplaying HOT 3
- 关于指标 HOT 1
- loss问题
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