CF-based web service recommender systems and QoS space visualization

Web services are software components designed to support interoperable machine-to-machine interaction over a network. The adoption of web services as a delivery mode in business has fostered a new paradigm shift from the development of monolithic applications to the dynamic setup of business process. The number of public web services is steadily increasing. Implementing service-oriented applications, service engineers (also called service users) usually get a list of web services from service brokers or search engines that meet the specific functional requirements. They need to identify the optimal one from the functionally equivalent candidates. Quality-of-Service (QoS) is widely employed to represent the nonfunctional performance of web services and has been considered as the key factor in service selection. a set of user-perceived properties including response time, availability, reputation, etc. the service candidates, since conducting real-world web service invocations is time consuming and resource-consuming. Besides client-side evaluation, it’s impractical to acquire QoS information from service providers or third-party communities, because service QoS performance is susceptible to the uncertain Internet environment and user context. Different users may observe quite different QoS performance of the same web service, and QoS values evaluated by one user cannot be used directly by another in service selection and recommendation. the functional equivalents. Several previous work has applied collaborative filtering (CF) to web service recommendation.