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An information-theoretic model for link prediction in complex networks
Various structural features of networks have been applied to develop link prediction methods. However, because different features highlight different aspects of network structural properties, it is very difficult to benefit from all of the features that might be available. In this paper, we investig...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4558573/ https://www.ncbi.nlm.nih.gov/pubmed/26335758 http://dx.doi.org/10.1038/srep13707 |
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author | Zhu, Boyao Xia, Yongxiang |
author_facet | Zhu, Boyao Xia, Yongxiang |
author_sort | Zhu, Boyao |
collection | PubMed |
description | Various structural features of networks have been applied to develop link prediction methods. However, because different features highlight different aspects of network structural properties, it is very difficult to benefit from all of the features that might be available. In this paper, we investigate the role of network topology in predicting missing links from the perspective of information theory. In this way, the contributions of different structural features to link prediction are measured in terms of their values of information. Then, an information-theoretic model is proposed that is applicable to multiple structural features. Furthermore, we design a novel link prediction index, called Neighbor Set Information (NSI), based on the information-theoretic model. According to our experimental results, the NSI index performs well in real-world networks, compared with other typical proximity indices. |
format | Online Article Text |
id | pubmed-4558573 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-45585732015-09-11 An information-theoretic model for link prediction in complex networks Zhu, Boyao Xia, Yongxiang Sci Rep Article Various structural features of networks have been applied to develop link prediction methods. However, because different features highlight different aspects of network structural properties, it is very difficult to benefit from all of the features that might be available. In this paper, we investigate the role of network topology in predicting missing links from the perspective of information theory. In this way, the contributions of different structural features to link prediction are measured in terms of their values of information. Then, an information-theoretic model is proposed that is applicable to multiple structural features. Furthermore, we design a novel link prediction index, called Neighbor Set Information (NSI), based on the information-theoretic model. According to our experimental results, the NSI index performs well in real-world networks, compared with other typical proximity indices. Nature Publishing Group 2015-09-03 /pmc/articles/PMC4558573/ /pubmed/26335758 http://dx.doi.org/10.1038/srep13707 Text en Copyright © 2015, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Zhu, Boyao Xia, Yongxiang An information-theoretic model for link prediction in complex networks |
title | An information-theoretic model for link prediction in complex networks |
title_full | An information-theoretic model for link prediction in complex networks |
title_fullStr | An information-theoretic model for link prediction in complex networks |
title_full_unstemmed | An information-theoretic model for link prediction in complex networks |
title_short | An information-theoretic model for link prediction in complex networks |
title_sort | information-theoretic model for link prediction in complex networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4558573/ https://www.ncbi.nlm.nih.gov/pubmed/26335758 http://dx.doi.org/10.1038/srep13707 |
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