Semantic Visualization to Support Knowledge Discovery in Multi-Relational Service Communities

Abstract

Services provided through the Internet serve a dual purpose. They are used by consumers and by technical systems to access business functionality, which is provided remotely by business partners. The semantics of services, multi-relational networked data and knowledge discovery in multi-relational service communities (e.g., service providers, service consumers, and service brokers, etc.) become an area of increasing interest. The complex multi-dimensional semantic relationship between services demands innovative and intuitive visualization techniques to present knowledge in a personalized manner, where community members can interact with knowledge assets and navigate through the network of Semantic Web services. In this chapter, the authors introduce Semantic Visualization approach (SemaVis) to support knowledge discovery by using hybrid recommender system (HYRES). It makes use of the semantic descriptions of the Web services, and also exploits the dynamic evolving relationships between services, service providers and service consumers. The authors introduce a sample scenario from a research project TEXO, within the THESEUS research program initiated by the German Federal Ministry of Economy and Technology (BMWi). It aims to supply a service-oriented architecture for the integration of Web-based services in the next generation of Business Value Networks. The authors present as well the application of their approaches SemaVis and HYRES to support knowledge discovery in multi-relational service communities of future Business Value Networks.