An Entropy-Based Self-Adaptive Node Importance Evaluation Method for Complex Networks
Identifying important nodes in complex networks is essential in disease transmission control, network attack protection, and valuable information detection. Many evaluation indicators, such as degree centrality, betweenness centrality, and closeness centrality, have been proposed to identify importa...
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/4529429 |
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| _version_ | 1850110564301275136 |
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| author | Qibo Sun Guoyu Yang Ao Zhou |
| author_facet | Qibo Sun Guoyu Yang Ao Zhou |
| author_sort | Qibo Sun |
| collection | DOAJ |
| description | Identifying important nodes in complex networks is essential in disease transmission control, network attack protection, and valuable information detection. Many evaluation indicators, such as degree centrality, betweenness centrality, and closeness centrality, have been proposed to identify important nodes. Some researchers assign different weight to different indicator and combine them together to obtain the final evaluation results. However, the weight is usually subjectively assigned based on the researcher’s experience, which may lead to inaccurate results. In this paper, we propose an entropy-based self-adaptive node importance evaluation method to evaluate node importance objectively. Firstly, based on complex network theory, we select four indicators to reflect different characteristics of the network structure. Secondly, we calculate the weights of different indicators based on information entropy theory. Finally, based on aforesaid steps, the node importance is obtained by weighted average method. The experimental results show that our method performs better than the existing methods. |
| format | Article |
| id | doaj-art-469bd01b58224a2e96e2a15751b26077 |
| institution | OA Journals |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-469bd01b58224a2e96e2a15751b260772025-08-20T02:37:48ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/45294294529429An Entropy-Based Self-Adaptive Node Importance Evaluation Method for Complex NetworksQibo Sun0Guoyu Yang1Ao Zhou2State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, ChinaState Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, ChinaState Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, ChinaIdentifying important nodes in complex networks is essential in disease transmission control, network attack protection, and valuable information detection. Many evaluation indicators, such as degree centrality, betweenness centrality, and closeness centrality, have been proposed to identify important nodes. Some researchers assign different weight to different indicator and combine them together to obtain the final evaluation results. However, the weight is usually subjectively assigned based on the researcher’s experience, which may lead to inaccurate results. In this paper, we propose an entropy-based self-adaptive node importance evaluation method to evaluate node importance objectively. Firstly, based on complex network theory, we select four indicators to reflect different characteristics of the network structure. Secondly, we calculate the weights of different indicators based on information entropy theory. Finally, based on aforesaid steps, the node importance is obtained by weighted average method. The experimental results show that our method performs better than the existing methods.http://dx.doi.org/10.1155/2020/4529429 |
| spellingShingle | Qibo Sun Guoyu Yang Ao Zhou An Entropy-Based Self-Adaptive Node Importance Evaluation Method for Complex Networks Complexity |
| title | An Entropy-Based Self-Adaptive Node Importance Evaluation Method for Complex Networks |
| title_full | An Entropy-Based Self-Adaptive Node Importance Evaluation Method for Complex Networks |
| title_fullStr | An Entropy-Based Self-Adaptive Node Importance Evaluation Method for Complex Networks |
| title_full_unstemmed | An Entropy-Based Self-Adaptive Node Importance Evaluation Method for Complex Networks |
| title_short | An Entropy-Based Self-Adaptive Node Importance Evaluation Method for Complex Networks |
| title_sort | entropy based self adaptive node importance evaluation method for complex networks |
| url | http://dx.doi.org/10.1155/2020/4529429 |
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