Top-n Recommendation

Top-N Recommendation is a recommendation task that, within the context of personalized information filtering, is distinguished by its objective of identifying and ranking the N most relevant items for a user, where N is a predefined positive integer.

217

Publications

16.8K

Citations

566

Authors

213

Institutions

Publications per year

2017–2026

119

Authors

566

  1. GK
    George Karypis

    University of Minnesota, United States

    8 publications · 1.8K citations

    8

    h-index

  2. SK
    Sang‐Wook Kim

    Hanyang University, South Korea

    7 publications · 310 citations

    7

    h-index

  3. WZ
    Weinan Zhang

    Shanghai Jiao Tong University, China

    6 publications · 223 citations

    6

    h-index

  4. YY
    Yong Yu

    Shanghai Jiao Tong University, China

    5 publications · 188 citations

    5

    h-index

  5. DL
    Dongsheng Li

    Fudan University, China

    5 publications · 94 citations

    5

    h-index

1–5 of 566

Venues

  1. arXiv (Cornell University)

    Repository · 9 publications · 169 citations

    9

    h-index

  2. IEEE Access

    8 publications · 207 citations

    8

    h-index

  3. Knowledge-Based Systems

    6 publications · 200 citations

    6

    h-index

  4. Neurocomputing

    5 publications · 187 citations

    5

    h-index

  5. Expert Systems with Applications

    5 publications · 139 citations

    5

    h-index

1–5