Knowledge Graph Evaluation

Knowledge Graph Evaluation is a systematic academic methodology for assessing the quality, completeness, and effectiveness of knowledge graphs through defined metrics and benchmarks that differentiate it from general data evaluation techniques by focusing specifically on symbolic knowledge representation, relational structure, and semantic accuracy.

71

Publications

4.9K

Citations

272

Authors

129

Institutions

Publications per year

2017–2026

60

Authors

272

  1. HP
    Heiko Paulheim

    University of Mannheim, Germany

    3 publications · 1.3K citations

    3

    h-index

  2. TB
    Taiyu Ban

    University of Science and Technology of China, China

    3 publications · 129 citations

    3

    h-index

  3. XW
    Xiangyu Wang

    University of Science and Technology of China, China

    3 publications · 129 citations

    3

    h-index

  4. LC
    Lyuzhou Chen

    University of Science and Technology of China, China

    3 publications · 129 citations

    3

    h-index

  5. HC
    Huanhuan Chen

    University of Science and Technology of China, China

    3 publications · 129 citations

    3

    h-index

1–5 of 272

Venues

  1. IEEE Access

    4 publications · 389 citations

    4

    h-index

  2. Information

    3 publications · 94 citations

    3

    h-index

  3. Semantic Web

    3 publications · 1.6K citations

    3

    h-index

  4. Journal of Web Semantics

    2 publications · 68 citations

    2

    h-index

  5. Knowledge-Based Systems

    2 publications · 160 citations

    2

    h-index

1–5