Volume 55, Number 1, January-February 2021
|Page(s)||77 - 97|
|Published online||18 February 2021|
Department of Mathematics “Tullio Levi-Civita”, University of Padua, Padova 35121, Italy
2 Consiglio Nazionale delle Ricerche – Istituto per le Applicazioni del Calcolo “M. Picone”, Naples, Italy
3 GSSI Gran Sasso Science Institute, L’Aquila 67100, Italy
* Corresponding author: email@example.com
Accepted: 5 October 2020
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.
Mathematics Subject Classification: 05C82 / 68R10 / 94C15 / 60J20
Key words: Complex network / nonlocal dynamics / Markov chain / Perron–Frobenius
© EDP Sciences, SMAI 2021
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