Knowledge-based Recommendation

Knowledge-Based Recommendation is a type of recommender system that generates suggestions by leveraging structured domain knowledge and explicit user preferences, distinguishing itself from other recommendation approaches through its reliance on inference mechanisms rather than historical or collaborative data patterns.

1.4K

Publications

72.6K

Citations

4.1K

Authors

1.1K

Institutions

Publications per year

2017–2026

932

Authors

4.1K

  1. XX
    Xing Xie

    Microsoft Research Asia (China), China

    20 publications · 6K citations

    18

    h-index

  2. AF
    Alexander Felfernig

    Graz University of Technology, Austria

    17 publications · 840 citations

    14

    h-index

  3. JW
    Ji-Rong Wen

    Renmin University of China, China

    14 publications · 2K citations

    14

    h-index

  4. WX
    Wayne Xin Zhao

    Renmin University of China, China

    12 publications · 1.9K citations

    13

    h-index

  5. GS
    Giovanni Semeraro

    University of Bari Aldo Moro, Italy

    10 publications · 425 citations

    11

    h-index

1–5 of 4.1K

Venues

  1. Expert Systems with Applications

    76 publications · 5.3K citations

    39

    h-index

  2. Knowledge-Based Systems

    45 publications · 2.7K citations

    29

    h-index

  3. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 29 publications · 2.9K citations

    22

    h-index

  4. Information Sciences

    27 publications · 1.2K citations

    21

    h-index

  5. IEEE Access

    29 publications · 1.2K citations

    18

    h-index

1–5