A similarity-based framework for service repository integration

Nowadays, repositories of services are becoming increasingly useful in the management of many public and private service provider organizations. In order to make a repository an integrated representation of all services delivered in an organization, a unified representation is desirable. Since several repositories of services, each potentially characterized by heterogeneous and conflicting representations, may coexist in the same organization or in cooperating organizations, the need for service repository integration techniques is emerging. In this paper, we investigate the problem of integrating heterogeneous service repositories. We first provide a conceptual model for describing services and semantic relationships among them. Then, we define a multi-level similarity function that is able to discover similarities between services belonging to different repositories, and to suggest candidate relationships among services. The proposed function combines a simple keyword-based matching with a more complex semantic matching that exploits the Explicit Semantic Analysis technique for generating a representation of services based on Wikipedia concepts. These combined techniques are implemented in the SCAn (Service Correspondence Analyzer) framework that supports the hunian expert during the repository integration process. The framework has been evaluated in a real-life scenario and the results demonstrate the effectiveness of the proposed approach.