ACM

doi:doi:10.57702/u1zw77gg

ACM

The dataset used in the paper is a heterogeneous graph, which is a graph that contains multiple types of nodes and edges. The dataset is used for semi-supervised graph learning with multi-level data augmentation.

BibTex:

@dataset{Yaming_Yang_and_Ziyu_Guan_and_Jianxin_Li_and_Wei_Zhao_and_Jiangtao_Cui_and_Quan_Wang_2024,
    abstract = {The dataset used in the paper is a heterogeneous graph, which is a graph that contains multiple types of nodes and edges. The dataset is used for semi-supervised graph learning with multi-level data augmentation.},
    author = {Yaming Yang and Ziyu Guan and Jianxin Li and Wei Zhao and Jiangtao Cui and Quan Wang},
    doi = {10.57702/u1zw77gg},
    institution = {No Organization},
    keyword = {'ACM', 'Academic Papers', 'Citation Network', 'Edges', 'Graph Clustering', 'Heterogeneous Graphs', 'Hypergraph Neural Network', 'Hypergraph Self-Attention Mechanism', 'Link Prediction', 'Multi-level Data Augmentation', 'Node Clustering', 'Node Features', 'Scientific Paper Classification', 'Semi-supervised Learning', 'heterogeneous information network', 'object classiﬁcation'},
    month = {nov},
    publisher = {TIB},
    title = {ACM},
    url = {https://service.tib.eu/ldmservice/dataset/acm},
    year = {2024}
}