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The supplementary dataset for the paper "Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking". We include the splits for cora, citeseer, and pubmed, the hard negative samples, and the node2vec embeddings. We also include a jupyter file read_data.ipynb to show how to read the non-txt file. heart_test_samples.npy, heart_valid_samples.npy: the heard negative samples *-n2v-embedding.pt: node2vec embeddings test_samples_index.pt, valid_samples_index.pt: the node index of the selected samples in ogbl-ppa under HeaRT gnn_feature: the input feature of cora, citeseer, pubmed More details for our code and how to use the dataset are on the code repository: https://github.com/Juanhui28/HeaRT .
link prediction, graph neural networks, benchmark, hard negative samples
link prediction, graph neural networks, benchmark, hard negative samples
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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| downloads | 6 |

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