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.