Link Prediction via Convex Nonnegative Matrix Factorization on Multiscale Blocks
Low rank matrices approximations have been used in link prediction for networks, which are usually global optimal methods and lack of using the local information. The block structure is a significant local feature of matrices: entities in the same block have similar values, which implies that links...
Saved in:
Main Authors: | Enming Dong, Jianping Li, Zheng Xie |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2014-01-01
|
Series: | Journal of Applied Mathematics |
Online Access: | http://dx.doi.org/10.1155/2014/786156 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Link Quality Prediction via a Neighborhood-Based Nonnegative Matrix Factorization Model for Wireless Sensor Networks
by: Yuxin Zhao, et al.
Published: (2015-10-01) -
Sparse Deep Nonnegative Matrix Factorization
by: Zhenxing Guo, et al.
Published: (2020-03-01) -
Feature Extraction for Evaluating the Complexity of Electromagnetic Environment Based on Adaptive Multiscale Morphological Gradient and Nonnegative Matrix Factorization
by: Hua-Chen Xi, et al.
Published: (2022-01-01) -
Discriminatively Constrained Semi-Supervised Multi-View Nonnegative Matrix Factorization with Graph Regularization
by: Guosheng Cui, et al.
Published: (2024-03-01) -
Incremental Graph Regulated Nonnegative Matrix Factorization for Face Recognition
by: Zhe-Zhou Yu, et al.
Published: (2014-01-01)