Header

UZH-Logo

Maintenance Infos

Link Prediction in Bipartite Nested Networks


Medo, Matúš; Mariani, Manuel Sebastian; Lü, Linyuan (2018). Link Prediction in Bipartite Nested Networks. Entropy, 20(10):777.

Abstract

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

Abstract

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

Statistics

Citations

Dimensions.ai Metrics
3 citations in Web of Science®
3 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

45 downloads since deposited on 28 Mar 2019
33 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Business Administration
08 Research Priority Programs > Social Networks
Dewey Decimal Classification:330 Economics
Scopus Subject Areas:Physical Sciences > General Physics and Astronomy
Language:English
Date:10 October 2018
Deposited On:28 Mar 2019 12:35
Last Modified:22 Jun 2020 20:05
Publisher:MDPI Publishing
ISSN:1099-4300
OA Status:Gold
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.3390/e20100777
Other Identification Number:merlin-id:16883

Download

Gold Open Access

Download PDF  'Link Prediction in Bipartite Nested Networks'.
Preview
Content: Published Version
Filetype: PDF
Size: 381kB
View at publisher
Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)