Basket Recommendation

Basket Recommendation is a computational method that, within the domain of market basket analysis, specifically generates personalized item suggestions for inclusion in a user's current or future transactional basket based on patterns of co-purchased items.

22

Publications

829

Citations

76

Authors

34

Institutions

Publications per year

2017–2026

15

Variants

Basket-based RecommendationMarket Basket Recommendation

Authors

76

  1. BD
    Benjamin Dias

    Unilever (United Kingdom), United Kingdom

    2 publications · 79 citations

    2

    h-index

  2. YF
    Yuan Fang

    Singapore Management University, Singapore

    2 publications · 117 citations

    2

    h-index

  3. HW
    Hady W. Lauw

    Singapore Management University, Singapore

    2 publications · 117 citations

    2

    h-index

  4. WE
    Wael El‐Deredy

    University of Manchester, United Kingdom

    2 publications · 79 citations

    2

    h-index

  5. PW
    Pengfei Wang

    Beijing University of Posts and Telecommunications, China

    2 publications · 158 citations

    2

    h-index

1–5 of 76

Venues

  1. IEEE Access

    1 publications · 15 citations

    1

    h-index

  2. Procedia - Social and Behavioral Sciences

    1 publications · 26 citations

    1

    h-index

  3. Journal on Data Semantics

    JoDS · 1 publications · 17 citations

    1

    h-index

  4. 1

    h-index

  5. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 1 publications · 24 citations

    1

    h-index

1–5