Applying Semi-Order Preference Model in Content-Based Service Discovery

Efficient service discovery is a crucial process for Web service utilization. Most existing service discovery approaches, based on either functional or non-functional attributes, do not address the issues associated with the impact of subjective expectations and preferences on service discovery. For example, duplicated and similar functionalities existing among services require service consumers to include additional aspects (i.e. content of service) to evaluate the services. The service consumers and providers often have different views on the content of services. This work attempts to alleviate their differences by proposing a multi-agent consensus approach which is based on fuzzy group decision making methods and semantic web technologies in order to assist service providers and consumers in discovering appropriate services with consideration of their expectations and preferences. In addition, a user-friendly tool for constructing agent-based Web service is introduced for assistance in representing user's preference and expectations and managing Web services.