Basics of PageRank algorithm have been widely adopted in its variations, tailored for specific scenarios. In this work, we consider the Black Hole metric, an extension of the original PageRank that leverages a (bogus) black hole node to reduce the arc weights normalization effect. We further extend this approach by introducing several black holes to investigate on the cohesiveness of the network, a measure of the strength among nodes belonging to the network. First experiments on real networks show the effectiveness of the proposed approach.

A pagerank inspired approach to measure network cohesiveness

Carchiolo V.;Grassia M.;Longheu A.;Malgeri M.;Mangioni G.
2019-01-01

Abstract

Basics of PageRank algorithm have been widely adopted in its variations, tailored for specific scenarios. In this work, we consider the Black Hole metric, an extension of the original PageRank that leverages a (bogus) black hole node to reduce the arc weights normalization effect. We further extend this approach by introducing several black holes to investigate on the cohesiveness of the network, a measure of the strength among nodes belonging to the network. First experiments on real networks show the effectiveness of the proposed approach.
2019
978-3-030-34913-4
978-3-030-34914-1
File in questo prodotto:
File Dimensione Formato  
IDCS_41.pdf

solo gestori archivio

Tipologia: Versione Editoriale (PDF)
Dimensione 1.06 MB
Formato Adobe PDF
1.06 MB Adobe PDF   Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/379358
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact