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--- |
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license: mit |
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task_categories: |
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- graph-ml |
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language: |
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- en |
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tags: |
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- graph |
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- knowledge |
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- citation |
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- network |
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- scholar |
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pretty_name: AceMap Academic Graph Dataset |
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size_categories: |
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- 1B<n<10B |
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--- |
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# AceMap Academic Graph Dataset |
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## Dataset Description |
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The AceMap Academic Graph Dataset is a large-scale academic citation network, containing **2,624,498,906 edges** and **264,675,127 nodes**. Each node represents an academic paper, and each edge indicates that one paper cites another. Each node can be linked to the [AceMap](https://acemap.info/) website for more detailed information. |
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## Dataset Source |
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This dataset is provided by: |
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- Wang, Xinbing, et al. "AceMap: Knowledge discovery through academic graph." arXiv preprint arXiv:2403.02576 (2024). |
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## Data Format |
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The dataset is provided in CSV file format, containing two columns: |
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- `id`: The unique identifier of the paper, in the form of `ZEJBRUdDQUdBRUI`. |
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- `referenced_works`: The unique identifier of the cited paper, in the form of `ZDlHREE5QjhCRkQ`. |
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## Data Examples |
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Here are some examples from the dataset: |
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| id | referenced_works | |
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|------------------------|--------------------------------| |
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| ZEJBRkNDRTg3RDk | ZDlHREE5QjhCRkQ | |
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| ZEJBRkNDRTg3RDk | ZDlHRTk4REVHN0E | |
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... |
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## Usage Instructions |
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### 0. Download from Huggingface |
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[https://huggingface.co/datasets/Reacubeth/acemap_citation_network](https://huggingface.co/datasets/Reacubeth/acemap_citation_network) |
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``` |
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git lfs install |
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git clone https://huggingface.co/datasets/Reacubeth/acemap_citation_network |
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``` |
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### 1. Unzip the `.tar.gz` Files |
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Use the `tar` command to extract the contents of each `.tar.gz` file. For example, to extract all files to a directory named `data`, you can run the following commands: |
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```bash |
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tar -xzvf filelist_part_aa.tar.gz -C data/ |
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tar -xzvf filelist_part_ab.tar.gz -C data/ |
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tar -xzvf filelist_part_ac.tar.gz -C data/ |
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tar -xzvf filelist_part_ad.tar.gz -C data/ |
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tar -xzvf filelist_part_ae.tar.gz -C data/ |
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``` |
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This will extract the CSV files to the `data/` directory. |
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### 2. Load the CSV Files |
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Use Pandas or other data processing tools to load the CSV files. Here is an example of how to load and concatenate all CSV files into a single DataFrame: |
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### 3. Access AceMap Website |
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For more detailed information about each paper, visit the [AceMap](https://acemap.info/) website by concatenating the following example strings: |
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```python |
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url = 'https://acemap.info/papers/' + 'ZEJBRkNDRTg3RDk' |
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``` |
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## Citation |
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If you use this dataset, please cite the following publication: |
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``` |
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@article{wang2024acemap, |
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title={AceMap: Knowledge discovery through academic graph}, |
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author={Wang, Xinbing and Fu, Luoyi and Gan, Xiaoying and Wen, Ying and Zheng, Guanjie and Ding, Jiaxin and Xiang, Liyao and Ye, Nanyang and Jin, Meng and Liang, Shiyu and others}, |
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journal={arXiv preprint arXiv:2403.02576}, |
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year={2024} |
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} |
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``` |
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## Contact |
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For any questions or further assistance, please contact email [email protected]. |
