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---
license: unknown
task_categories:
- graph-ml
tags:
- chemistry
configs:
- config_name: transductive
  data_files:
  - split: train
    path: "processed/transductive/train_df.csv"
  - split: valid
    path: "processed/transductive/val_df.csv"
  - split: test
    path: "processed/transductive/test_df.csv"
- config_name: inductive
  data_files:
  - split: train
    path: "processed/inductive/train_df.csv"
  - split: valid
    path: "processed/inductive/val_df.csv"
  - split: test
    path: "processed/inductive/test_df.csv"
- config_name: raw
  data_files: "raw/*.txt"
---

Source Paper: https://arxiv.org/abs/1802.06916

### Usage
```
from torch_geometric.datasets.cornell import CornellTemporalHyperGraphDataset

dataset = CornellTemporalHyperGraphDataset(root = "./", name="NDC-substances", split="train")
```

### Citation

```misc
@article{Benson-2018-simplicial,
 author = {Benson, Austin R. and Abebe, Rediet and Schaub, Michael T. and Jadbabaie, Ali and Kleinberg, Jon},
 title = {Simplicial closure and higher-order link prediction},
 year = {2018},
 doi = {10.1073/pnas.1800683115},
 publisher = {National Academy of Sciences},
 issn = {0027-8424},
 journal = {Proceedings of the National Academy of Sciences}
}
```