An Approach Based on Fuzzy Sets to Handle Preferences in Service Retrieval

Katia Abbaci (1) , Fernando Lemos (2) , Allel Hadjali (1) , Daniela Grigori (2) , Ludovic Lietard (1) , Daniel Rocacher (1) , Mokrane Bouzeghoub (2)

1 PILGRIM - Gradedness, Imprecision, and Mediation in Database Management Systems
2 PRISM - Parallélisme, Réseaux, Systèmes, Modélisation

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.

Domaines: Base de données [cs.DB]; Recherche d'information [cs.IR]; Web

Katia Abbaci, Fernando Lemos, Allel Hadjali, Daniela Grigori, Ludovic Lietard, et al.. An Approach Based on Fuzzy Sets to Handle Preferences in Service Retrieval. IEEE Conference on Commerce and Enterprise Computing, Sep 2011, Luxembourg. pp.213-218. ⟨hal-00672480⟩