An Approach Based on Fuzzy Sets to Selecting and Ranking Business Processes

Katia Abbaci 1 Fernando Lemos 2 Allel Hadjali 1 Daniela Grigori 2 Ludovic Liétard 1 Daniel Rocacher 1 Mokrane Bouzeghoub 2
1 PILGRIM - Gradedness, Imprecision, and Mediation in Database Management Systems
IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
2 PRISM - Parallélisme, Réseaux, Systèmes, Modélisation
Abstract : Current approaches for service discovery are based on semantic knowledge, such as ontologies and service behavior (described as a process model). However, these approaches have high selectivity rate, resulting in a large number of services offering similar functionalities and behavior. One way to improve the selectivity rate is to cope with user preferences defined on quality attributes. In this paper, we propose a novel approach for service retrieval that takes into account the service process model and relies both on preference satisfiability and structural similarity. User query and target process models are represented as annotated graphs, where user preferences on QoS attributes are modelled by means of fuzzy sets. A flexible evaluation strategy based on fuzzy linguistic quantifiers is introduced. Finally, different ranking methods are discussed.
Type de document :
Communication dans un congrès
IEEE 13th Conference on Commerce and Enterprise, Sep 2011, Luxembourg, Luxembourg. pp.213-218, 2011
Liste complète des métadonnées
https://hal.archives-ouvertes.fr/hal-00663438
Contributeur : Isabelle Moudenner Cohen <>
Soumis le : vendredi 27 janvier 2012 - 10:15:50
Dernière modification le : mardi 24 avril 2018 - 13:38:43

Identifiants

  • HAL Id : hal-00663438, version 1

Collections

IRISA | PRISM | UVSQ | IRISA-D7 | INRIA | UR1-UFR-ISTIC | UNIV-RENNES

Citation

Katia Abbaci, Fernando Lemos, Allel Hadjali, Daniela Grigori, Ludovic Liétard, et al.. An Approach Based on Fuzzy Sets to Selecting and Ranking Business Processes. IEEE 13th Conference on Commerce and Enterprise, Sep 2011, Luxembourg, Luxembourg. pp.213-218, 2011. 〈hal-00663438〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

342

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD