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Open AccessArticle

Link Prediction in Bipartite Nested Networks

1
Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054, China
2
Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, 3010 Bern, Switzerland
3
Department of Physics, University of Fribourg, 1700 Fribourg, Switzerland
4
URPP Social Networks, Universität Zürich, 8050 Zürich, Switzerland
5
Alibaba Research Center for Complexity Sciences, Hangzhou Normal University, Hangzhou 311121, China
*
Author to whom correspondence should be addressed.
Entropy 2018, 20(10), 777; https://doi.org/10.3390/e20100777
Received: 31 July 2018 / Revised: 8 October 2018 / Accepted: 8 October 2018 / Published: 10 October 2018
(This article belongs to the Special Issue Economic Fitness and Complexity)
Real networks typically studied in various research fields—ecology and economic complexity, for example—often exhibit a nested topology, which means that the neighborhoods of high-degree nodes tend to include the neighborhoods of low-degree nodes. Focusing on nested networks, we study the problem of link prediction in complex networks, which aims at identifying likely candidates for missing links. We find that a new method that takes network nestedness into account outperforms well-established link-prediction methods not only when the input networks are sufficiently nested, but also for networks where the nested structure is imperfect. Our study paves the way to search for optimal methods for link prediction in nested networks, which might be beneficial for World Trade and ecological network analysis. View Full-Text
Keywords: link prediction; nested networks; bipartite networks link prediction; nested networks; bipartite networks
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MDPI and ACS Style

Medo, M.; Mariani, M.S.; Lü, L. Link Prediction in Bipartite Nested Networks. Entropy 2018, 20, 777. https://doi.org/10.3390/e20100777

AMA Style

Medo M, Mariani MS, Lü L. Link Prediction in Bipartite Nested Networks. Entropy. 2018; 20(10):777. https://doi.org/10.3390/e20100777

Chicago/Turabian Style

Medo, Matúš; Mariani, Manuel S.; Lü, Linyuan. 2018. "Link Prediction in Bipartite Nested Networks" Entropy 20, no. 10: 777. https://doi.org/10.3390/e20100777

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