Cross-domain Collaborative Filtering
Cross-Domain Collaborative Filtering is a collaborative filtering approach that transfers user preference knowledge across distinct but related domains to improve recommendation accuracy in a target domain by leveraging auxiliary data from a source domain.
78
Publications
4.4K
Citations
219
Authors
94
Institutions
Publications per year
2017–2026
41
Variants
Cdcf
Parents
78
Personalized recommendation via cross-domain triadic factorization
Liang Hu, Jian Cao, Guandong Xu et al. · 2013 · 263 citations
Computing, Data Science, Data Mining +15
1–5 of 78
219
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Hong Kong University of Science and Technology, Hong Kong SAR China
5 publications · 1K citations
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5
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4
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4
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1–5 of 219
94
University of Technology Sydney
Sydney, Australia
8 h-index
14 publications
1K citations

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
7 h-index
17 publications
2K citations

Zhejiang University
Hangzhou, China
5 h-index
6 publications
125 citations
Fudan University
Shanghai, China
5 h-index
11 publications
1.7K citations
Qingdao University of Science and Technology
Qingdao, China
5 h-index
22 publications
2K citations
Dalian University of Technology
Dalian, China
3 h-index
6 publications
174 citations

Universidad Autónoma de Madrid
Madrid, Spain
3 h-index
5 publications
305 citations

University of Hong Kong
Pok Fu Lam, Hong Kong
3 h-index
9 publications
1K citations
1–8 of 94
6 publications · 182 citations
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2 publications · 69 citations
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Repository · 1 publications · 98 citations
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2 publications · 22 citations
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2 publications · 71 citations
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