Topic Interpretability

Topic Interpretability is a qualitative evaluation measure in topic modeling that assesses the degree to which the human-readable coherence and semantic meaning of inferred topics align with intuitive conceptual understanding.

26

Publications

3.1K

Citations

90

Authors

42

Institutions

Publications per year

2017–2026

14

Authors

90

  1. FM
    Fred Morstatter

    University of Southern California, United States

    2 publications · 41 citations

    2

    h-index

  2. AP
    Angga Pratama Sitorus

    University of Indonesia, Indonesia

    1 publications · 13 citations

    1

    h-index

  3. SC
    Shawn Chen

    Ohio University, United States

    1 publications · 39 citations

    1

    h-index

  4. LL
    Lisa Lee

    University of Edinburgh, United Kingdom

    1 publications · 25 citations

    1

    h-index

  5. ER
    Emil Rijcken

    University Medical Center Utrecht, Netherlands

    1 publications · 17 citations

    1

    h-index

1–5 of 90

Venues

  1. Expert Systems with Applications

    2 publications · 38 citations

    2

    h-index

  2. 1

    h-index

  3. PLoS ONE

    1 publications · 13 citations

    1

    h-index

  4. Computer Methods and Programs in Biomedicine

    1 publications · 39 citations

    1

    h-index

  5. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 1 publications · 47 citations

    1

    h-index

1–5