Measuring the similarity of labeled graphs

Abstract : This paper proposes a similarity measure to compare cases represented by labeled graphs. We first define an expressive model of directed labeled graph, allowing multiple labels on vertices and edges. Then we define the similarity problem as the search of a best mapping, where a mapping is a correspondence between vertices of the graphs. A key point of our approach is that this mapping does not have to be univalent, so that a vertex in a graph may be associated with several vertices of the other graph. Another key point is that the quality of the mapping is determined by generic functions, which can be tuned in order to implement domain-dependant knowledge. We discuss some computational issues related to this problem, and we describe a greedy algorithm for it. Finally, we show that our approach provides not only a quantitative measure of the similarity, but also qualitative information which can prove valuable in the adaptation phase of CBR.
Type de document :
Communication dans un congrès
Kevin D. Ashley and Derek G. Bridge. 5th Int. Conf. On Case-Based Reasoning (ICCBR 2003), Jun 2003, Trondheim (NO), Norway. Springer, pp.80-95, 2003, 〈10.1007/3-540-45006-8_9〉
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-01541469
Contributeur : Équipe Gestionnaire Des Publications Si Liris <>
Soumis le : lundi 19 juin 2017 - 11:00:27
Dernière modification le : jeudi 1 novembre 2018 - 01:20:37

Lien texte intégral

Identifiants

Collections

Citation

Pierre-Antoine Champin, Christine Solnon. Measuring the similarity of labeled graphs. Kevin D. Ashley and Derek G. Bridge. 5th Int. Conf. On Case-Based Reasoning (ICCBR 2003), Jun 2003, Trondheim (NO), Norway. Springer, pp.80-95, 2003, 〈10.1007/3-540-45006-8_9〉. 〈hal-01541469〉

Partager

Métriques

Consultations de la notice

144