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  1. .gitattributes +0 -1
  2. arxiv/arxiv.md +7 -0
  3. goodreads_children/LinkPrediction/10000/edge_split_hitsk.pt +3 -0
  4. goodreads_children/LinkPrediction/100000/edge_split_hitsk.pt +3 -0
  5. goodreads_children/LinkPrediction/5000/edge_split_hitsk.pt +3 -0
  6. goodreads_crime/LinkPrediction/5000/edge_split_hitsk.pt +3 -0
  7. goodreads_history/LinkPrediction/5000/edge_split_hitsk.pt +3 -0
  8. twitter/LinkPrediction/5000/edge_split_hitsk.pt +3 -0
.gitattributes CHANGED
@@ -75,5 +75,4 @@ reddit/raw/reddit.csv filter=lfs diff=lfs merge=lfs -text
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  amazon_apps/raw/Apps_for_Android_5.json filter=lfs diff=lfs merge=lfs -text
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  amazon_apps/raw/meta_Apps_for_Android.json filter=lfs diff=lfs merge=lfs -text
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  amazon_apps/emb/output_requests_apps_edge.jsonl filter=lfs diff=lfs merge=lfs -text
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- arxiv/dataset/ogbn_arxiv/processed/data_processed filter=lfs diff=lfs merge=lfs -text
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  goodreads_children/emb/output_requests_children_edge.jsonl filter=lfs diff=lfs merge=lfs -text
 
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  amazon_apps/raw/Apps_for_Android_5.json filter=lfs diff=lfs merge=lfs -text
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  amazon_apps/raw/meta_Apps_for_Android.json filter=lfs diff=lfs merge=lfs -text
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  amazon_apps/emb/output_requests_apps_edge.jsonl filter=lfs diff=lfs merge=lfs -text
 
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  goodreads_children/emb/output_requests_children_edge.jsonl filter=lfs diff=lfs merge=lfs -text
arxiv/arxiv.md CHANGED
@@ -16,3 +16,10 @@ Node classification tasks in the arxiv dataset include predicting the paper's ca
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  ## Data references
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  * Kuansan Wang, Zhihong Shen, Chiyuan Huang, Chieh-Han Wu, Yuxiao Dong, and Anshul Kanakia.Microsoft academic graph: When experts are not enough. Quantitative Science Studies, 1(1):396–413, 2020
 
 
 
 
 
 
 
 
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  ## Data references
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  * Kuansan Wang, Zhihong Shen, Chiyuan Huang, Chieh-Han Wu, Yuxiao Dong, and Anshul Kanakia.Microsoft academic graph: When experts are not enough. Quantitative Science Studies, 1(1):396–413, 2020
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+
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+ You can directly get the raw dataset from following codes:
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+
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+ ```python
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+ from ogb.nodeproppred import PygNodePropPredDataset
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+ dataset = PygNodePropPredDataset(name='ogbn-arxiv')
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+ ```
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