Finding useful services is a challenging and important task in several applications. Current approaches for services retrieval are mostly limited to the matching of their inputs/outputs. In this paper, we argue that in several applications (services having multiple and dependent operations and scientific workflows), the service discovery should be based on the specification of service behavior. The idea behind is to develop matching techniques that operate on behavior models and allow delivery of approximate matches and evaluation of semantic distance between these matches and the user requirements. To do so, we reduce the problem of behavioral matching to a graph matching problem and adapt existing algorithms for this purpose. To validate our approach, we developed a BPEL ranking platform that allows to find in a service repository, a set of service candidates satisfying user requirements, and then, to rank these candidates using a behavioral-based similarity measure.