Datasets:

daqh
/

email-Eu

@@ -56,7 +56,7 @@ In addition to the raw hypergraph topology, vector features are provided for bot
 - [Node2Vec](https://arxiv.org/abs/1607.00653) embeddings: random-walk–based structural embeddings.
 - [VilLain](https://dl.acm.org/doi/10.1145/3589334.3645454) embeddings: self-supervised hypergraph representation learning via virtual label propagation.
-Basic statistics (as packaged here): 327 nodes, 12,799 hyperedges, 1 connected component.
 ## Citation

 - [Node2Vec](https://arxiv.org/abs/1607.00653) embeddings: random-walk–based structural embeddings.
 - [VilLain](https://dl.acm.org/doi/10.1145/3589334.3645454) embeddings: self-supervised hypergraph representation learning via virtual label propagation.
+Basic statistics (as packaged here): 998 nodes, 25027 hyperedges, 20 connected component, largest connected component ratio 0.9809619238476954.
 ## Citation