An Expressive and Efficient Solution to the Service Selection Problem

Given the large number of Semantic Web Services that can be created from online sources by using existing annotation tools, expressive formalisms and efficient and scalable approaches to solve the service selection problem are required to make these services widely available to the users. In this paper, we propose a framework that is grounded on logic and the Local-As-View approach for representing instances of the service selection problem. In our approach, Web services are semantically described using LAV mappings in terms of generic concepts from an ontology, user requests correspond to conjunctive queries on the generic concepts and, in addition, the user may specify a set of preferences that are used to rank the possible solutions to the given request. The LAV formulation allows us to cast the service selection problem as a query rewriting problem that must consider the relationships among the concepts in the ontology and the ranks induced by the preferences. Then, building on related work, we devise an encoding of the resulting query rewriting problem as a logical theory whose models are in correspondence with the solutions of the user request, and in presence of preferences, whose best models are in correspondence with the best-ranked solutions. Thus, by exploiting known properties of modern SAT solvers, we provide an efficient and scalable solution to the service selection problem. The approach provides the basis to represent a large number of real-world situations and interesting user requests.