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Cognitive Radio Interference Modeling and Application on Fading Channels Read chapter Read first chapter

2015 | OriginalPaper | Chapter

62. Link Prediction via a Neighborhood-Based Nonnegative Matrix Factorization Model

Authors : Yuxin Zhao, Shenghong Li, Chenglin Zhao, Wen Jiang

Published in: The Proceedings of the Third International Conference on Communications, Signal Processing, and Systems

Publisher: Springer International Publishing

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Abstract

Link prediction is an important issue to understand the dynamics and evolution mechanisms of complex networks. Traditional link prediction algorithms are based on the topological properties of the underlying network in terms of graph theory. In order to improve the accuracy of link prediction, recent researches increasingly focus on modeling the link behaviors from the latent structure information of the networks. In this paper, we propose a neighborhood-based nonnegative matrix factorization model to solve the problem of link prediction. Our model learns latent feature factors from the overall topological structure combing with local neighborhood structures of the underlying network. Extensive experiments on real-world networks demonstrate the effectiveness and efficiency of our proposed model.

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previous chapter QoS Multi-path Routing Scheme Based on ACR Algorithm in Industrial Ethernet
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Metadata
Title
Link Prediction via a Neighborhood-Based Nonnegative Matrix Factorization Model
Authors
Yuxin Zhao
Shenghong Li
Chenglin Zhao
Wen Jiang
Copyright Year
2015
Book
The Proceedings of the Third International Conference on Communications, Signal Processing, and Systems

Print ISBN: 978-3-319-08990-4

Electronic ISBN: 978-3-319-08991-1

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-08991-1_62