DeepEye: Link Prediction in Dynamic Networks Based on Non-negative Matrix Factorization

DeepEye: Link Prediction in Dynamic Networks Based on Non-negative Matrix Factorization

A Non-negative Matrix Factorization (NMF)-based method is proposed to solve the link prediction problem in dynamic graphs. The method learns latent features from the temporal and topological structure of a dynamic network and can obtain higher prediction results. We present novel iterative rules to...

Полное описание

Библиографические подробности
Главные авторы: Nahla Mohamed Ahmed, Ling Chen, Yulong Wang, Bin Li, Yun Li, Wei Liu
Формат: Статья
Язык:English
Опубликовано: Tsinghua University Press 2018-03-01
Серии:Big Data Mining and Analytics
Предметы:
dynamic network
link prediction
matrix factorization
Online-ссылка:https://www.sciopen.com/article/10.26599/BDMA.2017.9020002

Internet

https://www.sciopen.com/article/10.26599/BDMA.2017.9020002

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