Making Temporal Betweenness Computation Faster and Restless-Reference-Cited by-同舟云学术

Making Temporal Betweenness Computation Faster and Restless

Published:2024-08-24 Issue: Volume:22 Page:163-174
ISSN:
Container-title:Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Brunelli Filippo¹^ORCID,Crescenzi Pierluigi²^ORCID,Viennot Laurent³^ORCID

Affiliation:

1. European Commission -- JRC, Seville, Spain

2. Gran Sasso Science Institute, L'Aquila, Italy

3. Inria, DI ENS, Paris, France

Funder

French ANR

PNRR MIUR

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3637528.3671825

Reference50 articles.

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3. Ruben Becker, Pierluigi Crescenzi, Antonio Cruciani, and Bojana Kodric. last checked on October 13, 2023 b. TSBProxy. https://github.com/piluc/TSBProxy.

4. Ferenc Béres, Róbert Pálovics, Anna Oláh, and András A Benczúr. 2018. Temporal walk based centrality metric for graph streams. Applied network science, Vol. 3, 1 (2018), 32:1--32:26.

5. Paolo Boldi, Massimo Santini, and Sebastiano Vigna. last checked on December 31, 2023. Crawdad. https://law.di.unimi.it.

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1. MANTRA: Temporal Betweenness Centrality Approximation Through Sampling;Lecture Notes in Computer Science;2024