Concepedia

Category Hierarchy Optimization

Category Hierarchy Optimization is a computational framework that systematically refines the structural organization of categories within a hierarchical taxonomy to maximize coherence, minimize redundancy, and enhance semantic accuracy in knowledge representation.

1

Publications

69

Citations

3

Authors

2

Institutions

Publications per year

2017–2026

0

Parents

Publications

1

1–1 of 1

Authors

3

  1. FL
    Fei Li

    Chengdu University of Technology, China

    1 publications · 69 citations

    1

    h-index

  2. BZ
    Bin Zhao

    Northwestern Polytechnical University, China

    1 publications · 69 citations

    1

    h-index

  3. EP
    Eric P. Xing

    Carnegie Mellon University, United States

    1 publications · 69 citations

    1

    h-index

1–3 of 3

Institutions

2

  1. Stanford University

    Stanford, United States

    1 h-index

    1 publications

    69 citations

  2. Carnegie Mellon University

    Pittsburgh, United States

    1 h-index

    2 publications

    138 citations

1–2 of 2