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Extending the Adapted PageRank Algorithm Centrality to Multiplex Networks with Data Using the PageRank Two-Layer Approach

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Extending the Adapted PageRank Algorithm Centrality to Multiplex Networks with Data Using the PageRank Two-Layer Approach

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Agryzkov, T.; Curado, M.; Pedroche Sánchez, F.; Tortosa, L.; Vicent, JF. (2019). Extending the Adapted PageRank Algorithm Centrality to Multiplex Networks with Data Using the PageRank Two-Layer Approach. Symmetry (Basel). 11(2):1-17. https://doi.org/10.3390/sym11020284

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/140416

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Title: Extending the Adapted PageRank Algorithm Centrality to Multiplex Networks with Data Using the PageRank Two-Layer Approach
Author: Agryzkov, Taras Curado, Manuel Pedroche Sánchez, Francisco Tortosa, Leandro Vicent, Jose F.
UPV Unit: Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada
Issued date:
Abstract:
[EN] Usually, the nodes' interactions in many complex networks need a more accurate mapping than simple links. For instance, in social networks, it may be possible to consider different relationships between people. This ...[+]
Subjects: Adapted PageRank algorithm , PageRank vector , Networks centrality , Multiplex networks , Biplex networks
Copyrigths: Reconocimiento (by)
Source:
Symmetry (Basel). (eissn: 2073-8994 )
DOI: 10.3390/sym11020284
Publisher:
MDPI AG
Publisher version: https://doi.org/10.3390/sym11020284
Project ID:
MICINN/TIN2017-84821-P
Thanks:
This research is partially supported by the Spanish Government, Ministerio de Economia y Competividad, grant number TIN2017-84821-P.
Type: Artículo

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