Semantic Web service descriptions are typically multiparameter constructs. Discovering semantically relevant services, given a desirable service description, is typically addressed by performing a pairwise logic-based match between the requested and offered parameters. However, little or no attention is given to combining these partial results to compile the final list of candidate services. Instead, this is often done in an ad hoc manner, implying a priori assumptions regarding the user’s preferences. In this paper, we focus on identifying the best candidate Semantic Web services given the description of a requested service. We model the problem as a skyline query, also known as the maximum vector problem, and we show how the service selection process can be performed efficiently. We consider different aspects, addressing both the requesters’ and the providers’ points of view. Experimental evaluation on real and synthetic data shows the effectiveness and efficiency of the pr...