Topic Clustering

Topic Clustering is a computational method in text analysis that organizes documents into coherent groups based on semantic similarity, distinguishing itself from other clustering techniques by focusing on latent thematic structures derived from textual content.

360

Publications

17.4K

Citations

1.1K

Authors

492

Institutions

Publications per year

2017–2026

151

Variants

Thematic Clustering

Authors

1.1K

  1. WG
    Wolfgang Glänzel

    KU Leuven, Belgium

    4 publications · 187 citations

    4

    h-index

  2. JH
    Jiawei Han

    University of Illinois Urbana-Champaign, United States

    4 publications · 224 citations

    4

    h-index

  3. SN
    Sharif Naser Makhadmeh

    Ajman University, United Arab Emirates

    3 publications · 62 citations

    3

    h-index

  4. TP
    Trefor P. Williams

    Rutgers, The State University of New Jersey, United States

    3 publications · 76 citations

    3

    h-index

  5. DP
    Dinh Phung

    Deakin University, Australia

    3 publications · 140 citations

    3

    h-index

1–5 of 1.1K

Venues

  1. Scientometrics

    12 publications · 683 citations

    12

    h-index

  2. Expert Systems with Applications

    8 publications · 214 citations

    8

    h-index

  3. Information Sciences

    6 publications · 148 citations

    6

    h-index

  4. Journal of Medical Internet Research

    4 publications · 292 citations

    4

    h-index

  5. PLoS ONE

    4 publications · 1.9K citations

    4

    h-index

1–5