Graph-based Expertise Matching

Graph-Based Expertise Matching is a methodological framework within expertise matching that models relationships between experts and domains as a structured graph, where nodes represent entities such as individuals, skills, or publications and edges encode semantic or collaborative associations, enabling the inference of expertise through graph-theoretic analysis.

3

Publications

51

Citations

9

Authors

3

Institutions

Publications per year

2017–2026

1

Authors

9

  1. JC
    Jayne Curson

    University of Leeds, United Kingdom

    1 publications · 16 citations

    1

    h-index

  2. JT
    Jie Tang

    Tsinghua University, China

    1 publications · 12 citations

    1

    h-index

  3. EW
    Ernesto William De Luca

    Technische Universität Berlin, Germany

    1 publications · 23 citations

    1

    h-index

  4. KW
    Kan Wu

    Sun Yat-sen University, China

    1 publications · 12 citations

    1

    h-index

  5. AA
    Akram Alkouz

    Princess Sumaya University for Technology, Jordan

    1 publications · 23 citations

    1

    h-index

1–5 of 9

Institutions

3

  1. Tsinghua University

    Beijing, China

    1 h-index

    3 publications

    36 citations

  2. University of Leeds

    Leeds, United Kingdom

    1 h-index

    3 publications

    48 citations

  3. Massachusetts Institute of Technology

    Cambridge, United States

    1 h-index

    1 publications

    12 citations

1–3 of 3

Venues

  1. Knowledge and Information Systems

    1 publications · 16 citations

    1

    h-index

1–1