DATA WAREHOUSES FOR SEMANTIC WEB SERVICE MATCHMAKING

With the rapidly growing number of web services, clients are presented with a range of alternatives of functionally similar (or even identical) services. This range of choices allows clients to select services that match their requirements and criteria. In general, a web service has two types of properties namely, functional and non-functional properties. The functional properties describe what the service can do; whereas the non¬functional properties depict how the service can be done. Non¬functional properties involve qualitative or quantitative features that are essential criteria to enhance the selection process of services. In this paper we provide a matchmaking method that can identify the best candidate semantic web service(s) given the description of the requested service(s). In addition, our proposed approach presents a ranking for those services. We model the problem using data warehouses and we show how the selection process can be performed efficiently based on functional, non¬functional properties, and user preferences, along with the help of data warehousing techniques. Finally, we present an experimental evaluation that investigates both the effectiveness and efficiency of the proposed approach