Hybrid Filtering
Hybrid Filtering is a filtering approach that integrates multiple distinct information filtering techniques—such as collaborative, content-based, and knowledge-based methods—within a unified framework to overcome the limitations of individual approaches and improve overall recommendation accuracy and robustness.
281
Publications
15.8K
Citations
795
Authors
341
Institutions
Publications per year
2017–2026
111
Parents
281
Combining Content-Based and Collaborative Filters in an Online Newspaper
Mark Claypool, Anuja Gokhale, Tim Miranda et al. · 1999 · 782 citations
Content-based, collaborative recommendation
Marko Balabanović, Yoav Shoham · 1997 · 413 citations
Ana Belén Barragáns Martínez, Enrique Costa‐Montenegro, Juan C. Burguillo et al. · Information Sciences · 2010 · 353 citations
1–5 of 281
795
Aristotle University of Thessaloniki, Greece
3 publications · 337 citations
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3
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3
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3
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2
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1–5 of 795
341

Huazhong University of Science and Technology
Wuhan, China
4 h-index
9 publications
252 citations

Harbin Institute of Technology
Harbin, China
4 h-index
9 publications
254 citations

Imperial College London
London, United Kingdom
3 h-index
11 publications
245 citations
Xiamen University
Xiamen, China
3 h-index
9 publications
164 citations

University of Electronic Science and Technology of China
Chengdu, China
3 h-index
11 publications
200 citations

Brunel University of London
London, United Kingdom
3 h-index
7 publications
311 citations
Binus University
Jakarta, Indonesia
3 h-index
7 publications
105 citations
Kumoh National Institute of Technology
Gumi, South Korea
3 h-index
8 publications
972 citations
1–8 of 341
10 publications · 746 citations
11
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7 publications · 664 citations
7
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4 publications · 655 citations
4
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3 publications · 338 citations
3
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3 publications · 71 citations
3
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1–5