SauravMaheshkar/contact-high-school

---
license: unknown
task_categories:
- graph-ml
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="contact-high-school", 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}
}
```

许可证：未知
任务类别：
- 图机器学习（graph-ml）
配置项：
- 配置名称：直推式（transductive）
数据文件：
- 拆分集：训练集，路径：processed/transductive/train_df.csv
- 拆分集：验证集，路径：processed/transductive/val_df.csv
- 拆分集：测试集，路径：processed/transductive/test_df.csv
- 配置名称：归纳式（inductive）
数据文件：
- 拆分集：训练集，路径：processed/inductive/train_df.csv
- 拆分集：验证集，路径：processed/inductive/val_df.csv
- 拆分集：测试集，路径：processed/inductive/test_df.csv
- 配置名称：原始（raw）
数据文件：raw/*.txt

来源论文：https://arxiv.org/abs/1802.06916

### 使用方法

from torch_geometric.datasets.cornell import CornellTemporalHyperGraphDataset

dataset = CornellTemporalHyperGraphDataset(root = "./", name="contact-high-school", split="train")

### 引用格式
misc
@article{Benson-2018-simplicial,
author = {Benson, Austin R. and Abebe, Rediet and Schaub, Michael T. and Jadbabaie, Ali and Kleinberg, Jon},
title = {单纯形闭包与高阶链路预测},
year = {2018},
doi = {10.1073/pnas.1800683115},
publisher = {National Academy of Sciences},
issn = {0027-8424},
journal = {美国国家科学院院刊}
}

原始信息汇总

数据集概述

许可证

• 许可证: 未知

任务类别

• 任务类别: 图机器学习（graph-ml）

配置信息

• 配置名称: transductive

  • 训练数据文件: processed/transductive/train_df.csv
  • 验证数据文件: processed/transductive/val_df.csv
  • 测试数据文件: processed/transductive/test_df.csv

• 配置名称: inductive

  • 训练数据文件: processed/inductive/train_df.csv
  • 验证数据文件: processed/inductive/val_df.csv
  • 测试数据文件: processed/inductive/test_df.csv

• 配置名称: raw

  • 原始数据文件: raw/*.txt

数据集使用示例

python from torch_geometric.datasets.cornell import CornellTemporalHyperGraphDataset

dataset = CornellTemporalHyperGraphDataset(root = "./", name="contact-high-school", split="train")

引用信息

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} }

搜集汇总

背景与挑战

背景概述

该数据集名为'contact-high-school'，由SauravMaheshkar创建，主要用于图机器学习任务，包含表格和文本两种模态。数据集规模在10万到100万之间，源自arXiv论文1802.06916，提供了训练、验证和测试三种子集划分。