Comprehensive Evaluation of Algorithms for Unrestricted Graph Alignment

Konstantinos Skitsas, Karol Orłowski, Judith Hermanns, Davide Mottin, Panagiotis Karras

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Abstract

The graph alignment problem calls for finding a matching between the nodes of one graph and those of another graph, in a way that they correspond to each other by some fitness measure. Over the last years, several graph alignment algorithms have been proposed and evaluated on diverse datasets and quality measures. Typically, a newly proposed algorithm is compared to previously proposed ones on some specific datasets, types of noise, and quality measures where the new proposal achieves superiority over the previous ones. However, no systematic comparison of the proposed algorithms has been attempted on the same benchmarks. This paper fills this gap by conducting an extensive, thorough, and commensurable evaluation of state-ofthe- art graph alignment algorithms. Our results highlight the value of overlooked solutions and an unprecedented effect of graph density on performance, hence call for further work.

OriginalsprogEngelsk
TitelProceedings 26th International Conference on Extending Database Technology (EDBT 2023)
Antal sider13
Forlagopenproceedings.org
Publikationsdato2023
Sider260-272
ISBN (Trykt)978-3-89318-088-2
DOI
StatusUdgivet - 2023
Begivenhed26th International Conference on Extending Database Technology, EDBT 2023 - Ioannina, Grækenland
Varighed: 28 mar. 202331 mar. 2023

Konference

Konference26th International Conference on Extending Database Technology, EDBT 2023
Land/OmrådeGrækenland
ByIoannina
Periode28/03/202331/03/2023
NavnProceedings of the 21st International Conference on Extending Database Technology (EDBT),
Vol/bind26
ISSN2367-2005

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