Session-based Content Recommendation

Session-Based Content Recommendation is a type of content-based recommendation approach that generates personalized content suggestions within a specific user session by modeling sequential interactions and contextual dependencies without relying on long-term user profiles.

56

Publications

2.2K

Citations

222

Authors

94

Institutions

Publications per year

2017–2026

53

Authors

222

  1. DJ
    Dietmar Jannach

    University of Klagenfurt, Austria

    5 publications · 602 citations

    5

    h-index

  2. ML
    Malte Ludewig

    TU Dortmund University, Germany

    3 publications · 364 citations

    3

    h-index

  3. YW
    Yan Wang

    Macquarie University, Australia

    3 publications · 202 citations

    3

    h-index

  4. BW
    Bang Wang

    Huazhong University of Science and Technology, China

    2 publications · 36 citations

    2

    h-index

  5. QZ
    Quan Z. Sheng

    Macquarie University, Australia

    2 publications · 171 citations

    2

    h-index

1–5 of 222

Venues

  1. Neurocomputing

    9 publications · 220 citations

    9

    h-index

  2. Knowledge-Based Systems

    7 publications · 190 citations

    7

    h-index

  3. Expert Systems with Applications

    6 publications · 264 citations

    6

    h-index

  4. User Modeling and User-Adapted Interaction

    4 publications · 588 citations

    4

    h-index

  5. Information Sciences

    3 publications · 62 citations

    3

    h-index

1–5