Concepedia

Model-based Collaborative Filtering

Model-Based Collaborative Filtering is a collaborative filtering approach that belongs to the class of methods utilizing explicit models derived from user-item interaction data, distinguished by its reliance on learned representations or latent factors—typically generated via matrix factorization, deep learning, or probabilistic frameworks—to predict missing ratings or preferences, as opposed to memory-based methods that directly use neighborhood heuristics.

159

Publications

17K

Citations

480

Authors

223

Institutions

Publications per year

2017–2026

62

Parents

Publications

159

A Survey of Collaborative Filtering Techniques

Xiaoyuan Su, Taghi M. Khoshgoftaar · Advances in Artificial Intelligence · 2009 · 3.6K citations · Full text

, , +16

Item-based top-<i>N</i>recommendation algorithms

Mukund Deshpande, George Karypis · ACM Transactions on Information Systems · 2004 · 2.2K citations

, , +13

AutoRec

Suvash Sedhain, Aditya Krishna Menon, Scott Sanner et al. · 2015 · 1.2K citations

, , +9

Multiverse recommendation

Alexandros Karatzoglou, Xavier Amatriain, Linas Baltrunas et al. · 2010 · 731 citations

, , +11

Scalable collaborative filtering using cluster-based smoothing

Gui-Rong Xue, Chenxi Lin, Qiang Yang et al. · 2005 · 665 citations

, , +14

1–5 of 159

Authors

480

  1. JB
    Jesús Bobadilla

    Universidad Politécnica de Madrid, Spain

    5 publications · 309 citations

    5

    h-index

  2. FO
    Fernando Ortega

    Universidad Politécnica de Madrid, Spain

    5 publications · 329 citations

    5

    h-index

  3. GK
    George Karypis

    University of Minnesota, United States

    3 publications · 2.4K citations

    3

    h-index

  4. JC
    Jamie Callan

    Carnegie Mellon University, United States

    3 publications · 227 citations

    3

    h-index

  5. CZ
    ChengXiang Zhai

    University of Illinois Urbana-Champaign, United States

    3 publications · 229 citations

    3

    h-index

1–5 of 480

Institutions

223

  1. Universidad Politécnica de Madrid

    Madrid, Spain

    6 h-index

    17 publications

    1.3K citations

  2. Carnegie Mellon University

    Pittsburgh, United States

    5 h-index

    14 publications

    1.1K citations

  3. Chinese Academy of Sciences

    Beijing, China

    5 h-index

    10 publications

    540 citations

  4. Shanghai Jiao Tong University

    Shanghai, China

    4 h-index

    11 publications

    2.1K citations

  5. University of Minnesota

    Minneapolis, United States

    4 h-index

    7 publications

    2.4K citations

  6. Microsoft (United States)

    Redmond, United States

    4 h-index

    5 publications

    2.1K citations

  7. University of Electronic Science and Technology of China

    Chengdu, China

    4 h-index

    10 publications

    237 citations

  8. University College Dublin

    Dublin, Ireland

    3 h-index

    6 publications

    184 citations

1–8 of 223

Venues

  1. IEEE Access

    9 publications · 793 citations

    9

    h-index

  2. Expert Systems with Applications

    7 publications · 643 citations

    7

    h-index

  3. Neural Computing and Applications

    3 publications · 182 citations

    3

    h-index

  4. 3

    h-index

  5. Knowledge-Based Systems

    3 publications · 163 citations

    3

    h-index

1–5