Nonlocal PageRank
Nonlocal PageRank
In this work we introduce and study a nonlocal version of the PageRank. In our approach, the random walker explores the graph using longer excursions than just moving between neighboring nodes. As a result, the corresponding ranking of the nodes, which takes into account a long-range interaction between them, does not exhibit concentration phenomena typical of spectral rankings which take into account just local interactions. We show that the predictive value of the rankings obtained using our proposals is considerably improved on different real world problems.
Complex network, Markov chain, Nonlocal dynamics, Perron-Frobenius
77-97
Cipolla, Stefano
373fdd4b-520f-485c-b36d-f75ce33d4e05
Durastante, Fabio
56118788-83b2-4273-b959-c45f486f86c1
Tudisco, Francesco
3c9b5744-c949-402e-ad23-b9f053c62e37
Cipolla, Stefano
373fdd4b-520f-485c-b36d-f75ce33d4e05
Durastante, Fabio
56118788-83b2-4273-b959-c45f486f86c1
Tudisco, Francesco
3c9b5744-c949-402e-ad23-b9f053c62e37
Cipolla, Stefano, Durastante, Fabio and Tudisco, Francesco
(2021)
Nonlocal PageRank.
ESAIM: Mathematical Modelling and Numerical Analysis, 55 (1), .
(doi:10.1051/m2an/2020071).
Abstract
In this work we introduce and study a nonlocal version of the PageRank. In our approach, the random walker explores the graph using longer excursions than just moving between neighboring nodes. As a result, the corresponding ranking of the nodes, which takes into account a long-range interaction between them, does not exhibit concentration phenomena typical of spectral rankings which take into account just local interactions. We show that the predictive value of the rankings obtained using our proposals is considerably improved on different real world problems.
Text
m2an200017
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Accepted/In Press date: 5 October 2020
e-pub ahead of print date: 18 February 2021
Keywords:
Complex network, Markov chain, Nonlocal dynamics, Perron-Frobenius
Identifiers
Local EPrints ID: 485534
URI: http://eprints.soton.ac.uk/id/eprint/485534
ISSN: 2822-7840
PURE UUID: e39e61ba-7e53-4683-a01d-15817e5aafd7
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Date deposited: 08 Dec 2023 17:41
Last modified: 18 Mar 2024 04:17
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Contributors
Author:
Stefano Cipolla
Author:
Fabio Durastante
Author:
Francesco Tudisco
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