Aarhus University Seal / Aarhus Universitets segl

Boosting Graph Alignment Algorithms

Publikation: Bidrag til bog/antologi/rapport/proceedingKonferencebidrag i proceedingsForskningpeer review

DOI

The problem of graph alignment is to find corresponding nodes between a pair of graphs. Past work has treated the problem in a monolithic fashion, with the graph as input and the alignment as output, offering limited opportunities to adapt the algorithm to task requirements or input graph characteristics. Recently, node embedding techniques are utilized for graph alignment. In this paper, we study two state-of-the-art graph alignment algorithms utilizing node representations, CONE-Align and GRASP, and describe them in terms of an overarching modular framework. In a targeted experimental study, we exploit this modularity to develop enhanced algorithm variants that are more effective in the alignment task.

OriginalsprogEngelsk
TitelProceedings of the 30th ACM International Conference on Information & Knowledge Management (CIKM '21)
Antal sider5
UdgivelsesstedNew York
ForlagAssociation for Computing Machinery
Udgivelsesårokt. 2021
Sider3166-3170
ISBN (Elektronisk)9781450384469
DOI
StatusUdgivet - okt. 2021
Begivenhed30th ACM International Conference on Information and Knowledge Management, CIKM 2021 - Virtual, Online, Australien
Varighed: 1 nov. 20215 nov. 2021

Konference

Konference30th ACM International Conference on Information and Knowledge Management, CIKM 2021
LandAustralien
ByVirtual, Online
Periode01/11/202105/11/2021
SponsorACM SIGIR, ACM, SigWEB

Se relationer på Aarhus Universitet Citationsformater

ID: 226898717