Search Query Data Mining

Search Query Data Mining is a computational methodology that systematically extracts, analyzes, and interprets patterns, trends, and relationships from large-scale collections of user-generated search queries to uncover latent information-seeking behaviors and contextual knowledge structures inherent in Internet search activities.

51

Publications

8K

Citations

154

Authors

90

Institutions

Publications per year

2017–2026

13

Authors

154

  1. KF
    Klaus F. Zimmermann

    IZA - Institute of Labor Economics, Germany

    4 publications · 687 citations

    4

    h-index

  2. WX
    Wei Xu

    Renmin University of China, China

    3 publications · 73 citations

    3

    h-index

  3. TD
    Thomas Dimpfl

    University of Tübingen, Germany

    3 publications · 407 citations

    3

    h-index

  4. SJ
    Stephan Jank

    Deutsche Bundesbank, Germany

    3 publications · 407 citations

    3

    h-index

  5. LV
    Liwen Vaughan

    Western University, Canada

    3 publications · 190 citations

    3

    h-index

1–5 of 154

Venues

  1. Journal of Medical Internet Research

    6 publications · 291 citations

    6

    h-index

  2. SSRN Electronic Journal

    Repository · 5 publications · 305 citations

    5

    h-index

  3. Clinical Infectious Diseases

    CID · 2 publications · 108 citations

    2

    h-index

  4. 2

    h-index

  5. European Archives of Oto-Rhino-Laryngology

    1 publications · 24 citations

    1

    h-index

1–5