Heterogeneous Graph Features

Heterogeneous Graph Features is a graph representation construct that encapsulates node and edge attributes in graphs with multiple types of entities and relations, enabling the differentiation of structural and semantic heterogeneity inherent in complex relational data.

114

Publications

10.7K

Citations

473

Authors

177

Institutions

Publications per year

2017–2026

98

Authors

473

  1. CS
    Chuan Shi

    Beijing University of Posts and Telecommunications, China

    4 publications · 3.5K citations

    4

    h-index

  2. YY
    Yanfang Ye

    Case Western Reserve University, United States

    4 publications · 3.2K citations

    4

    h-index

  3. TZ
    Tiangang Zhang

    Heilongjiang University, China

    3 publications · 98 citations

    3

    h-index

  4. PX
    Ping Xuan

    Heilongjiang University of Science and Technology, China

    3 publications · 98 citations

    3

    h-index

  5. HJ
    Houye Ji

    Beijing University of Posts and Telecommunications, China

    3 publications · 3.2K citations

    3

    h-index

1–5 of 473

Venues

  1. arXiv (Cornell University)

    Repository · 8 publications · 179 citations

    8

    h-index

  2. Briefings in Bioinformatics

    5 publications · 379 citations

    5

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 5 publications · 607 citations

    5

    h-index

  4. Bioinformatics

    4 publications · 333 citations

    4

    h-index

  5. 3

    h-index

1–5