|
--- |
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license: unknown |
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task_categories: |
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- graph-ml |
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configs: |
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- config_name: transductive |
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data_files: |
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- split: train |
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path: processed/transductive/train_df.csv |
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- split: valid |
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path: processed/transductive/val_df.csv |
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- split: test |
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path: processed/transductive/test_df.csv |
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- config_name: inductive |
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data_files: |
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- split: train |
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path: processed/inductive/train_df.csv |
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- split: valid |
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path: processed/inductive/val_df.csv |
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- split: test |
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path: processed/inductive/test_df.csv |
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- config_name: raw |
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data_files: raw/*.txt |
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--- |
|
|
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Source Paper: https://arxiv.org/abs/1802.06916 |
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|
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### Usage |
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``` |
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from torch_geometric.datasets.cornell import CornellTemporalHyperGraphDataset |
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|
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dataset = CornellTemporalHyperGraphDataset(root = "./", name="email-Enron-25", split="train") |
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``` |
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|
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### Citation |
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|
|
```misc |
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@article{Benson-2018-simplicial, |
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author = {Benson, Austin R. and Abebe, Rediet and Schaub, Michael T. and Jadbabaie, Ali and Kleinberg, Jon}, |
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title = {Simplicial closure and higher-order link prediction}, |
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year = {2018}, |
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doi = {10.1073/pnas.1800683115}, |
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publisher = {National Academy of Sciences}, |
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issn = {0027-8424}, |
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journal = {Proceedings of the National Academy of Sciences} |
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} |
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``` |
