A generative model for sparse, evolving digraphs

Papoudakis, Georgios; Preux, Philippe; Monperrus, Martin

Type de document :

Communication dans un congrès avec actes

DOI :

10.1007/978-3-319-72150-7_43

Titre :

A generative model for sparse, evolving digraphs

Auteur(s) :

Papoudakis, Georgios [Auteur]
Sequential Learning [SEQUEL]
Preux, Philippe [Auteur]

Sequential Learning [SEQUEL]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Monperrus, Martin [Auteur]

KTH Royal Institute of Technology [Stockholm] [KTH]

Titre de la manifestation scientifique :

6th International Conference on Complex Networks and their Applications

Ville :

Lyon

Pays :

France

Date de début de la manifestation scientifique :

2017-11-29

Discipline(s) HAL :

Informatique [cs]/Algorithme et structure de données [cs.DS]

Résumé en anglais : [en]

Generating graphs that are similar to real ones is an open problem, while the similarity notion is quite elusive and hard to formalize. In this paper, we focus on sparse digraphs and propose SDG, an algorithm that aims at ...
Lire la suite >Generating graphs that are similar to real ones is an open problem, while the similarity notion is quite elusive and hard to formalize. In this paper, we focus on sparse digraphs and propose SDG, an algorithm that aims at generating graphs similar to real ones. Since real graphs are evolving and this evolution is important to study in order to understand the underlying dynamical system, we tackle the problem of generating series of graphs. We propose SEDGE, an algorithm meant to generate series of graphs similar to a real series. SEDGE is an extension of SDG. We consider graphs that are representations of software programs and show experimentally that our approach outperforms other existing approaches. Experiments show the performance of both algorithms.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL

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1710.06298
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A generative model for sparse, evolving digraphs

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