Constraint-aware Recommendation

Constraint-Aware Recommendation is a type of patient-specific recommendation system that incorporates explicit clinical, logistical, or personal constraints into the recommendation process to ensure generated suggestions are feasible and compliant with real-world healthcare requirements.

12

Publications

813

Citations

47

Authors

10

Institutions

Publications per year

2017–2026

3

Authors

47

  1. AF
    Alexander Felfernig

    Graz University of Technology, Austria

    5 publications · 311 citations

    5

    h-index

  2. MZ
    Markus Zanker

    University of Klagenfurt, Austria

    3 publications · 99 citations

    3

    h-index

  3. KI
    Klaus Isak

    University of Klagenfurt, Austria

    2 publications · 28 citations

    2

    h-index

  4. WP
    Wolfgang P. Schmid

    University of Klagenfurt, Austria

    2 publications · 62 citations

    2

    h-index

  5. MM
    Monika Mandl

    Graz University of Technology, Austria

    2 publications · 25 citations

    2

    h-index

1–5 of 47

Venues

  1. AI Communications

    AICOM · 1 publications · 15 citations

    1

    h-index

  2. Knowledge-Based Systems

    1 publications · 119 citations

    1

    h-index

  3. Conference on Recommender Systems

    Conference · 1 publications · 13 citations

    1

    h-index

  4. ACM Transactions on Information Systems

    1 publications · 151 citations

    1

    h-index

  5. Journal of Emerging Technologies in Web Intelligence

    JETWI · 1 publications · 17 citations

    1

    h-index

1–5