Customer Embedding
Customer Embedding is a numerical representation technique that maps individual customer attributes and behaviors into a continuous, low-dimensional vector space to preserve relational and sequential patterns for predictive modeling in customer profiling.
4
Publications
100
Citations
16
Authors
8
Institutions
Publications per year
2017–2026
4
Parents
4
TriATNE: Tripartite Adversarial Training for Network Embeddings
Qidong Liu, Cheng Long, Jie Zhang et al. · IEEE Transactions on Cybernetics · 2021 · 16 citations
1–4 of 4
16
1
h-index
1
h-index
1
h-index
1
h-index
1
h-index
1–5 of 16
8

Zhengzhou University
Zhengzhou, China
1 h-index
3 publications
48 citations
University of Wuppertal
Wuppertal, Germany
1 h-index
3 publications
57 citations
UiT The Arctic University of Norway
Tromsø, Norway
1 h-index
3 publications
105 citations
Courant Institute of Mathematical Sciences
New York, United States
1 h-index
2 publications
60 citations
Nanyang Technological University
Singapore, Singapore
1 h-index
3 publications
48 citations

Norwegian Computing Center
Oslo, Norway
1 h-index
3 publications
105 citations
New York University
New York, United States
1 h-index
3 publications
90 citations
ProteinSimple (United States)
San Jose, United States
1 h-index
1 publications
19 citations
1–8 of 8
1 publications · 30 citations
1
h-index
1 publications · 16 citations
1
h-index
Repository · 1 publications · 35 citations
1
h-index
Conference · 1 publications · 19 citations
1
h-index
1–4