Graph-based Implicit Recommendation
Graph-Based Implicit Recommendation is a recommendation method that models user-item interactions as a graph structure to capture implicit feedback signals, distinguishing itself by leveraging relational dependencies among users and items through graph-based propagation and learning mechanisms.
6
Publications
212
Citations
25
Authors
9
Institutions
Publications per year
2017–2026
4
Parents
6
Arnold Adimabua Ojugo, Debby Oghenevwede Otakore · IAES International Journal of Artificial Intelligence · 2020 · 30 citations · Full text
1–5 of 6
25
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Federal University of Petroleum Resource Effurun, Nigeria
1 publications · 30 citations
1
h-index
1–5 of 25
9
Nanjing University
Nanjing, China
1 h-index
4 publications
40 citations
Federal University of Petroleum Resource Effurun
Warri, Nigeria
1 h-index
2 publications
60 citations
Huawei Technologies (Canada)
Markham, Canada
1 h-index
3 publications
267 citations

Shomal University
Āmol, Iran
1 h-index
2 publications
68 citations

Central South University
Changsha, China
1 h-index
3 publications
99 citations
Huawei Technologies (China)
Shenzhen, China
1 h-index
6 publications
534 citations

Universidad Autónoma de Madrid
Madrid, Spain
1 h-index
1 publications
16 citations

University of Glasgow
Glasgow, United Kingdom
1 h-index
3 publications
48 citations
1–8 of 9
1 publications · 33 citations
1
h-index
IJAI · 1 publications · 30 citations
1
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1 publications · 34 citations
1
h-index
1 publications · 10 citations
1–4