HyperGraph Datasets
Collection
Collection of HyperGraph Datasets
•
17 items
•
Updated
•
7
Datasets:
Dataset Viewer
hyperedge
int64 1
190k
| nodes
stringlengths 3
30
| timestamp
float64 2.23B
222B
|
|---|---|---|
1 |
[1, 2]
| 48,942,985,907 |
2 |
[3, 4, 5]
| 48,944,035,260 |
3 |
[8, 6, 7]
| 48,944,144,880 |
4 |
[9, 10, 11, 12, 13]
| 48,944,145,834 |
5 |
[14, 15]
| 48,944,187,157 |
6 |
[16, 17, 18]
| 48,944,205,644 |
7 |
[19, 20]
| 48,944,330,880 |
8 |
[4, 21]
| 48,944,354,450 |
9 |
[19]
| 48,944,481,514 |
11 |
[4]
| 48,944,534,724 |
13 |
[29, 6]
| 48,944,834,137 |
14 |
[9]
| 48,944,952,167 |
15 |
[4, 30]
| 48,944,959,450 |
16 |
[9, 31]
| 48,945,107,917 |
17 |
[8, 33, 32]
| 48,945,113,064 |
18 |
[34, 35]
| 48,945,144,514 |
19 |
[36]
| 48,945,186,367 |
20 |
[16, 37, 38]
| 48,945,256,474 |
23 |
[43, 44, 45]
| 48,945,511,970 |
24 |
[48, 46, 47]
| 48,945,607,677 |
26 |
[50, 51]
| 48,945,733,584 |
27 |
[52, 22, 6]
| 48,945,920,147 |
28 |
[53, 54, 55]
| 48,945,955,744 |
30 |
[16, 60]
| 48,946,176,780 |
31 |
[61]
| 48,946,339,690 |
32 |
[26, 27, 62]
| 48,946,564,720 |
33 |
[64, 61, 63]
| 48,946,619,744 |
34 |
[65, 53]
| 48,946,675,544 |
37 |
[72, 70, 71]
| 48,946,988,324 |
38 |
[73, 74, 75, 76, 22]
| 48,946,998,637 |
39 |
[74, 61]
| 48,947,032,427 |
41 |
[80, 70, 79]
| 48,947,342,804 |
43 |
[48, 11, 83]
| 48,948,225,670 |
44 |
[84]
| 48,948,274,730 |
45 |
[88, 85, 86, 87]
| 48,948,541,164 |
46 |
[89, 90, 91]
| 48,948,852,977 |
47 |
[92, 93, 94]
| 48,949,722,770 |
49 |
[8]
| 48,949,959,017 |
50 |
[88, 43]
| 48,950,347,864 |
51 |
[98, 99]
| 48,950,665,277 |
54 |
[105, 106, 107]
| 48,952,227,240 |
55 |
[61, 53]
| 48,952,874,667 |
56 |
[108, 109, 110, 111]
| 48,953,179,814 |
57 |
[112]
| 48,954,399,190 |
58 |
[9, 53, 113]
| 48,955,193,814 |
59 |
[114, 115, 19, 116, 117]
| 48,955,324,920 |
60 |
[17, 85, 118]
| 48,956,419,580 |
61 |
[19, 11, 61, 53]
| 48,956,526,910 |
62 |
[98, 67, 119]
| 48,956,969,194 |
63 |
[120]
| 48,957,937,124 |
64 |
[121]
| 48,958,056,900 |
65 |
[122, 123]
| 48,958,445,144 |
66 |
[124, 125]
| 48,959,543,584 |
67 |
[65, 126, 127]
| 48,959,754,950 |
68 |
[128, 129, 61, 6]
| 48,960,049,667 |
69 |
[130]
| 48,960,509,340 |
70 |
[131, 132]
| 48,960,663,750 |
71 |
[133]
| 48,960,793,434 |
72 |
[131, 134, 135, 136, 61]
| 48,960,877,427 |
73 |
[8, 137]
| 48,968,038,744 |
74 |
[89, 138, 139, 22]
| 48,968,130,580 |
75 |
[56, 115, 140]
| 48,968,181,717 |
76 |
[141, 142]
| 48,968,713,800 |
77 |
[144, 129, 143]
| 48,969,424,787 |
78 |
[145, 146]
| 48,971,200,144 |
80 |
[16, 149, 150]
| 48,976,454,354 |
81 |
[151]
| 48,978,196,057 |
82 |
[32, 137, 153, 152]
| 48,979,860,160 |
84 |
[156, 67, 155, 21]
| 48,981,673,324 |
86 |
[6, 9, 22, 61, 159]
| 48,983,038,287 |
88 |
[54]
| 48,990,918,130 |
89 |
[161, 162, 163, 164, 37]
| 48,991,950,427 |
90 |
[45, 165, 166, 167]
| 48,992,876,384 |
92 |
[128, 169]
| 48,993,706,864 |
93 |
[9, 6]
| 48,994,239,937 |
94 |
[170, 171]
| 48,994,854,467 |
95 |
[169, 172, 110, 81, 63]
| 48,996,467,760 |
96 |
[173, 174]
| 48,997,537,827 |
97 |
[11, 175]
| 48,998,882,644 |
98 |
[176, 153]
| 48,999,089,237 |
99 |
[4]
| 49,001,358,260 |
100 |
[177, 178, 92, 165]
| 49,002,262,744 |
101 |
[4]
| 49,003,165,357 |
102 |
[98, 12]
| 49,004,472,504 |
103 |
[179, 180]
| 49,004,505,874 |
104 |
[181]
| 49,006,275,674 |
106 |
[41, 183]
| 49,008,103,050 |
107 |
[184, 61]
| 49,008,866,937 |
108 |
[185, 12]
| 49,009,217,484 |
109 |
[2, 41, 42, 49, 26]
| 49,010,024,347 |
110 |
[186, 26]
| 49,010,229,207 |
111 |
[8, 57, 176]
| 49,012,073,500 |
112 |
[155, 187, 181]
| 49,013,836,660 |
113 |
[1, 125, 157]
| 49,019,070,544 |
115 |
[57, 187]
| 49,022,223,057 |
116 |
[16, 41]
| 49,024,137,374 |
117 |
[190, 14]
| 49,024,827,307 |
118 |
[14, 191]
| 49,027,870,027 |
119 |
[192, 193, 194]
| 49,028,743,494 |
121 |
[26, 197, 198]
| 49,035,067,647 |
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in Data Studio
Source Paper: https://arxiv.org/abs/1802.06916
Usage
from torch_geometric.datasets.cornell import CornellTemporalHyperGraphDataset
dataset = CornellTemporalHyperGraphDataset(root = "./", name="tags-ask-ubuntu", split="train")
Citation
@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}
}
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Size of downloaded dataset files:
17.5 MB
Size of the auto-converted Parquet files:
11.1 MB
Number of rows:
468,051