Keyword Recommendation

Keyword Recommendation is a computational method that identifies and suggests contextually relevant terms or phrases to represent the core content of a document or text, distinguishing itself from related information retrieval techniques by focusing specifically on proposing keywords that are not already present in the source material.

46

Publications

1.8K

Citations

154

Authors

71

Institutions

Publications per year

2017–2026

15

Authors

154

  1. CJ
    Chang-Ho Jeon

    Hanyang University, South Korea

    2 publications · 44 citations

    2

    h-index

  2. GX
    Gui-Rong Xue

    Shanghai Jiao Tong University, China

    2 publications · 136 citations

    2

    h-index

  3. KH
    Kwanghee Hong

    Hanyang University, South Korea

    2 publications · 44 citations

    2

    h-index

  4. ÉS
    Érik Saule

    The Ohio State University, United States

    1 publications · 28 citations

    2

    h-index

  5. JL
    Jie Lü

    University of Technology Sydney, Australia

    1 publications · 62 citations

    1

    h-index

1–5 of 154

Venues

  1. AI Communications

    AICOM · 2 publications · 238 citations

    2

    h-index

  2. Journal of Physics Conference Series

    1 publications · 26 citations

    1

    h-index

  3. ACM Transactions on the Web

    TWEB · 1 publications · 18 citations

    1

    h-index

  4. Information Research

    1 publications · 12 citations

    1

    h-index

  5. Multimedia Tools and Applications

    1 publications · 28 citations

    1

    h-index

1–5