Cross-context Recommendation

Cross-Context Recommendation is a type of context-aware recommendation approach that integrates and transfers knowledge across different contextual domains or settings to improve recommendation accuracy and adaptability by leveraging contextual information from sources beyond the target context.

34

Publications

1.9K

Citations

136

Authors

63

Institutions

Publications per year

2017–2026

20

Authors

136

  1. TH
    Tim Hussein

    University of Duisburg-Essen, Germany

    2 publications · 82 citations

    2

    h-index

  2. GA
    Gediminas Adomavičius

    University of Minnesota, United States

    2 publications · 49 citations

    2

    h-index

  3. WW
    Wei Wang

    Dalian University of Technology, China

    1 publications · 33 citations

    1

    h-index

  4. GZ
    Guangquan Zhang

    University of Technology Sydney, Australia

    1 publications · 35 citations

    1

    h-index

  5. MZ
    Min Zhang

    Dalian University of Technology, China

    1 publications · 25 citations

    1

    h-index

1–5 of 136

Venues

  1. Expert Systems with Applications

    3 publications · 96 citations

    3

    h-index

  2. Knowledge-Based Systems

    3 publications · 349 citations

    3

    h-index

  3. User Modeling and User-Adapted Interaction

    3 publications · 162 citations

    3

    h-index

  4. 1

    h-index

  5. Information Processing & Management

    1 publications · 65 citations

    1

    h-index

1–5