Event Recommendation Systems

Event Recommendation Systems is a computational framework within event management systems that personalizes event suggestions to users by analyzing their preferences, behaviors, and contextual data, distinguishing it from general recommendation systems through its specialized focus on event-specific attributes such as time, location, attendance dynamics, and temporal constraints.

92

Publications

3.6K

Citations

271

Authors

124

Institutions

Publications per year

2017–2026

34

Authors

271

  1. CZ
    Chuan Zhou

    Chinese Academy of Sciences, China

    5 publications · 272 citations

    5

    h-index

  2. LS
    Larisa Shwartz

    IBM Research - Thomas J. Watson Research Center, United States

    4 publications · 111 citations

    4

    h-index

  3. BW
    Bang Wang

    Huazhong University of Science and Technology, China

    4 publications · 98 citations

    4

    h-index

  4. MX
    Minghua Xu

    Huazhong University of Science and Technology, China

    4 publications · 129 citations

    4

    h-index

  5. TL
    Tao Li

    Florida International University, United States

    4 publications · 111 citations

    4

    h-index

1–5 of 271

Venues

  1. IEEE Access

    4 publications · 102 citations

    4

    h-index

  2. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 4 publications · 124 citations

    4

    h-index

  3. Information Sciences

    4 publications · 89 citations

    4

    h-index

  4. Multimedia Tools and Applications

    2 publications · 43 citations

    2

    h-index

  5. Ghent University Academic Bibliography (Ghent University)

    Repository · 2 publications · 48 citations

    2

    h-index

1–5