Datasets:

SauravMaheshkar
/

contact-high-school

hyperedge int64 1 120k	nodes stringlengths 6 25	timestamp float64 0 255k
1	[1, 2]	0
2	[9, 11]	0
4	[45, 46]	0
7	[41, 42]	0
8	[28, 29]	0
9	[57, 58]	0
10	[59, 60]	0
11	[8, 7]	0
12	[18, 19, 20]	0
13	[14, 15]	0
14	[30, 31]	0
16	[51, 52]	0
17	[34, 35]	0
19	[49, 50]	0
20	[44, 45]	0
21	[36, 37]	0
22	[3, 4]	0
23	[12, 13]	0
24	[53, 54]	0
25	[48, 47]	0
26	[9, 10]	0
27	[43, 15]	0
28	[16, 61]	0
29	[36, 38]	0
30	[21, 22]	0
31	[27, 22]	0
32	[5, 6]	0
33	[24, 23]	0
34	[67, 68]	20
35	[1, 2]	20
36	[9, 11]	20
38	[45, 46]	20
41	[66, 7]	20
43	[41, 42]	20
44	[59, 60]	20
45	[8, 7]	20
46	[74, 75]	20
47	[18, 19, 20]	20
48	[37, 70]	20
50	[67, 69]	20
51	[34, 35]	20
53	[49, 50]	20
54	[44, 45]	20
55	[37, 7]	20
56	[3, 4]	20
57	[12, 13]	20
58	[53, 54]	20
59	[48, 47]	20
61	[9, 10]	20
62	[43, 15]	20
63	[16, 61]	20
64	[62, 63]	20
65	[27, 22]	20
66	[5, 6]	20
67	[24, 23]	20
68	[72, 73]	20
69	[1, 2]	40
70	[9, 11]	40
71	[44, 45, 46]	40
74	[66, 7]	40
76	[58, 78]	40
77	[41, 42]	40
78	[59, 60]	40
79	[8, 7]	40
80	[18, 19, 20]	40
81	[14, 15]	40
83	[78, 79]	40
84	[37, 70]	40
86	[51, 52]	40
87	[67, 69]	40
88	[34, 35]	40
89	[82, 83]	40
91	[49, 50]	40
92	[37, 7]	40
93	[3, 4]	40
94	[12, 13]	40
95	[53, 54]	40
97	[80, 81]	40
98	[3, 7]	40
99	[9, 10]	40
100	[43, 15]	40
101	[16, 61]	40
102	[21, 22]	40
103	[27, 22]	40
104	[5, 6]	40
105	[24, 23]	40
106	[1, 2]	60
107	[10, 11]	60
108	[44, 45, 46]	60
109	[28, 85]	60
111	[66, 7]	60
114	[41, 42]	60
115	[59, 60]	60
116	[8, 7]	60
117	[57, 84]	60
118	[18, 19, 20]	60
119	[43, 14, 15]	60
120	[30, 31]	60
121	[78, 79]	60
123	[51, 52]	60

End of preview. Expand in Dataset Viewer.

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

@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}
}

Downloads last month: 45

Size of downloaded dataset files:

8.07 MB

Size of the auto-converted Parquet files:

2.62 MB

Number of rows:

297,224

Collection including SauravMaheshkar/contact-high-school

HyperGraph Datasets

Collection

Collection of HyperGraph Datasets • 17 items • Updated Apr 4 • 7