Communication publiée dans un ouvrage (Colloques, congrès, conférences scientifiques et actes)
Analyzing Complex Data in Motion at Scale with Temporal Graphs
HARTMANN, Thomas; FOUQUET, François; JIMENEZ, Matthieu et al.
2017In Proceedings of the 29th International Conference on Software Engineering and Knowledge Engineering
Peer reviewed
 

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Mots-clés :
data analytics; graph databases; large-scale graphs; time-evolving graphs
Résumé :
[en] Modern analytics solutions succeed to understand and predict phenomenons in a large diversity of software systems, from social networks to Internet-of-Things platforms. This success challenges analytics algorithms to deal with more and more complex data, which can be structured as graphs and evolve over time. However, the underlying data storage systems that support large-scale data analytics, such as time-series or graph databases, fail to accommodate both dimensions, which limits the integration of more advanced analysis taking into account the history of complex graphs, for example. This paper therefore introduces a formal and practical definition of temporal graphs. Temporal graphs pro- vide a compact representation of time-evolving graphs that can be used to analyze complex data in motion. In particular, we demonstrate with our open-source implementation, named GREYCAT, that the performance of temporal graphs allows analytics solutions to deal with rapidly evolving large-scale graphs.
Disciplines :
Sciences informatiques
Auteur, co-auteur :
HARTMANN, Thomas ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
FOUQUET, François ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
JIMENEZ, Matthieu  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Rouvoy, Romain;  University of Lille / Inria / IUF
LE TRAON, Yves ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
Analyzing Complex Data in Motion at Scale with Temporal Graphs
Date de publication/diffusion :
juillet 2017
Nom de la manifestation :
29th International Conference on Software Engineering and Knowledge Engineering
Lieu de la manifestation :
Pittsburgh, Etats-Unis
Date de la manifestation :
05-07-2017 to-07-07-2017
Titre de l'ouvrage principal :
Proceedings of the 29th International Conference on Software Engineering and Knowledge Engineering
Peer reviewed :
Peer reviewed
Focus Area :
Computational Sciences
Disponible sur ORBilu :
depuis le 24 juillet 2017

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citations Scopus®
 
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