Author-topic Models

Author-Topic Models is a probabilistic topic model that extends the Latent Dirichlet Allocation framework by incorporating authorship information to model the association between authors and topics in document collections.

267

Publications

24.8K

Citations

746

Authors

296

Institutions

Publications per year

2017–2026

96

Variants

Author-topic Model

Authors

746

  1. CL
    C. Lee Giles

    Pennsylvania State University, United States

    7 publications · 511 citations

    7

    h-index

  2. MS
    Mark Steyvers

    University of California, Irvine, United States

    7 publications · 8.4K citations

    7

    h-index

  3. DA
    Daniel A. McFarland

    Stanford University, United States

    5 publications · 264 citations

    5

    h-index

  4. AM
    Andrew McCallum

    University of Massachusetts Amherst, United States

    4 publications · 718 citations

    4

    h-index

  5. PM
    Prasenjit Mitra

    Pennsylvania State University, United States

    4 publications · 251 citations

    4

    h-index

1–5 of 746

Venues

  1. arXiv (Cornell University)

    Repository · 8 publications · 254 citations

    8

    h-index

  2. Neurocomputing

    8 publications · 137 citations

    8

    h-index

  3. Information Sciences

    6 publications · 198 citations

    6

    h-index

  4. Expert Systems with Applications

    6 publications · 217 citations

    6

    h-index

  5. Information Processing & Management

    6 publications · 492 citations

    6

    h-index

1–5