Context-aware E-commerce Recommendation

Context-Aware E-Commerce Recommendation is a recommendation framework that integrates situational and environmental factors—such as user location, time, device, or social context—into the personalization process to enhance the relevance of product suggestions within online shopping platforms, distinguishing itself from conventional e-commerce recommendation approaches by explicitly modeling dynamic contextual conditions influencing user preferences.

17

Publications

573

Citations

50

Authors

31

Institutions

Publications per year

2017–2026

7

Authors

50

  1. JK
    Joonmo Kim

    Dankook University, South Korea

    1 publications · 33 citations

    1

    h-index

  2. GV
    Gilles Vandelle

    Centre National de la Recherche Scientifique, France

    1 publications · 23 citations

    1

    h-index

  3. YS
    Yang Sok Kim

    Keimyung University, South Korea

    1 publications · 246 citations

    1

    h-index

  4. LB
    Lokesh B. Bhajantri

    REVA University, India

    1 publications · 11 citations

    1

    h-index

  5. VV
    Valeria Viserta

    Roma Tre University, Italy

    1 publications · 27 citations

    1

    h-index

1–5 of 50

Venues

  1. Expert Systems with Applications

    1 publications · 11 citations

    1

    h-index

  2. IT Professional

    1 publications · 12 citations

    1

    h-index

  3. Journal of Intelligent Information Systems

    1 publications · 41 citations

    1

    h-index

  4. Electronic Commerce Research

    1 publications · 25 citations

    1

    h-index

  5. Electronic Markets

    EM · 1 publications · 27 citations

    1

    h-index

1–5