Context-aware Web Recommendation

Context-Aware Web Recommendation is a recommendation approach that extends traditional web recommendation by incorporating contextual information—such as user location, time, device, or social environment—to dynamically adapt suggestions, thereby improving relevance and personalization in web-based systems.

48

Publications

2K

Citations

176

Authors

88

Institutions

Publications per year

2017–2026

15

Authors

176

  1. AL
    Antonis Loizou

    Vrije Universiteit Amsterdam, Netherlands

    2 publications · 42 citations

    2

    h-index

  2. PB
    Patrick Brézillon

    Sorbonne Université, France

    2 publications · 52 citations

    2

    h-index

  3. WC
    Wenbo Chen

    Lanzhou University, China

    2 publications · 52 citations

    2

    h-index

  4. DG
    David Gotz

    University of North Carolina at Chapel Hill, United States

    2 publications · 33 citations

    2

    h-index

  5. DJ
    Dietmar Jannach

    University of Klagenfurt, Austria

    2 publications · 85 citations

    2

    h-index

1–5 of 176

Venues

  1. Expert Systems with Applications

    2 publications · 125 citations

    2

    h-index

  2. Decision Support Systems

    2 publications · 172 citations

    2

    h-index

  3. Industrial Marketing Management

    1 publications · 322 citations

    1

    h-index

  4. Data Archiving and Networked Services (DANS)

    Repository · 1 publications · 12 citations

    1

    h-index

  5. Applied Soft Computing

    1 publications · 33 citations

    1

    h-index

1–5