Multiplex Network Embedding Model with High-Order Node Dependence
Article Properties
-
LanguageEnglish
-
DOI (url)
-
Publication Date2021/03/06
-
Journal
-
Indian UGC (journal)
-
Refrences56
-
Nianwen Ning Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, No. 10 Xitucheng Road, Beijing 100876, China ORCID
-
Qiuyue Li Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, No. 10 Xitucheng Road, Beijing 100876, China
-
Kai Zhao Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, No. 10 Xitucheng Road, Beijing 100876, China
-
Bin Wu Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, No. 10 Xitucheng Road, Beijing 100876, China ORCID
Abstract
Cite
Ning, Nianwen, et al. “Multiplex Network Embedding Model With High-Order Node Dependence”. Complexity, vol. 2021, 2021, pp. 1-18, https://doi.org/10.1155/2021/6644111.
Ning, N., Li, Q., Zhao, K., & Wu, B. (2021). Multiplex Network Embedding Model with High-Order Node Dependence. Complexity, 2021, 1-18. https://doi.org/10.1155/2021/6644111
Ning, Nianwen, Qiuyue Li, Kai Zhao, and Bin Wu. “Multiplex Network Embedding Model With High-Order Node Dependence”. Complexity 2021 (2021): 1-18. https://doi.org/10.1155/2021/6644111.
Ning N, Li Q, Zhao K, Wu B. Multiplex Network Embedding Model with High-Order Node Dependence. Complexity. 2021;2021:1-18.
Journal Categories
Science
Mathematics
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
Science
Science (General)
You May Also Like
- Review on Methods to Fix Number of Hidden Neurons in Neural Networks
- DEMATEL Technique: A Systematic Review of the State-of-the-Art Literature on Methodologies and Applications
- Landslide Susceptibility Assessment in Vietnam Using Support Vector Machines, Decision Tree, and Naïve Bayes Models
- On Riemann-Liouville and Caputo Derivatives
- Optimization Solution of Troesch’s and Bratu’s Problems of Ordinary Type Using Novel Continuous Genetic Algorithm
Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| The relationship between online social network ties and user attributes | 2021 | |||
| 10.1007/978-3-030-12528-8 | 2019 | |||
| Inductive representation learning on large graphs | 2017 | |||
| mvn2vec: preservation and collaboration in multi-view network embedding | Knowledge-Based Systems |
| 2020 | |
| Learning cross-domain representation with multi-graph neural network | 2019 |