Item Attribute Modeling
Item Attribute Modeling is a methodological framework within multi-criteria recommendation that characterizes items through structured representations of their intrinsic features, distinguishing itself by explicitly modeling attribute-level preferences to support fine-grained, criterion-aware recommendation decisions.
17
Publications
645
Citations
79
Authors
37
Institutions
Publications per year
2017–2026
11
17
FeatureMF: An Item Feature Enriched Matrix Factorization Model for Item Recommendation
Haiyang Zhang, Nikola S. Nikolov, Zhanlin Ji et al. · IEEE Access · 2021 · 41 citations · Full text
Applying probabilistic latent semantic analysis to multi-criteria recommender system
Yin Zhang⋆, Yueting Zhuang, Jiangqin Wu et al. · AI Communications · 2009 · 35 citations
1–5 of 17
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37

University of Minnesota
Minneapolis, United States
2 h-index
2 publications
203 citations
Tencent (China)
Shenzhen, China
2 h-index
3 publications
63 citations
Wuhan University
Wuhan, China
2 h-index
4 publications
171 citations
Columbia University
New York, United States
2 h-index
6 publications
609 citations
Volkswagen Financial Services (Germany)
Braunschweig, Germany
1 h-index
1 publications
14 citations
University of Technology Sydney
Sydney, Australia
1 h-index
3 publications
81 citations

North China University of Science and Technology
Tangshan, China
1 h-index
1 publications
41 citations
Universidade de Santiago de Compostela
Santiago de Compostela, Spain
1 h-index
5 publications
75 citations
1–8 of 37
Conference · 2 publications · 64 citations
2
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2 publications · 56 citations
2
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Conference · 1 publications · 28 citations
1
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Conference · 1 publications · 24 citations
1
h-index
1 publications · 24 citations
1
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1–5