Cited By
View all- Wang JYang ZCheng Z(2024)Deep Pre-Training Transformers for Scientific Paper RepresentationElectronics10.3390/electronics1311212313:11(2123)Online publication date: 29-May-2024
Network representation learning is an important tool for extracting latent features from heterogeneous networks to enhance downstream analysis tasks. However, for heterogeneous networks in the era of big data, their heterogeneity, unseen network ...
Heterogeneous information networks usually contain different kinds of nodes and distinguishing types of relations, which can preserve more information than homogeneous information networks. Heterogeneous network representation learning ...
Network embedding (NE), also known as network representation learning (NRL), is a method to learn a low-dimensional latent representation of nodes in an information network. The real-world data is usually presented in the form of heterogeneous ...
Association for Computing Machinery
New York, NY, United States
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in