Local Structure and High-Order Feature Preserved Network Embedding Based on Non-Negative Matrix Factorization

Local Structure and High-Order Feature Preserved Network Embedding Based on Non-Negative Matrix Factorization

Network embedding, as an effective method of learning the low-dimensional representations of nodes, has been widely applied to various complex network analysis tasks, such as node classification, community detection, link prediction and evolution analysis. The existing embedding methods usually focu...

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Bibliographic Details
Main Authors: Qin Tian, Lin Pan, Xuan Guo, Xiaoming Li, Wei Yu, Faming Li
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Network embedding
local structure
high-order feature
non-negative matrix factorization
Online Access:https://ieeexplore.ieee.org/document/9296805/

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