Semantic Web-based Context-aware Service Selection in Task-computing

Abstract

The hierarchy of task-computing and the decomposition strategy of complex task are analyzed according to the characteristics of task-computing in pervasive environment. The architecture relies on the semantic representation of service and content, however, the semantic representation is based on shared ontology. It can not only improve the accuracy and recall, but also realize the functions such as knowledge sharing, capability-based search, autonomous reasoning and semantic matchmaking. Thus, a dynamic semantic Web-based context aware service selection mechanism is proposed to filter and rank the matching services according to their dynamic context in order to optimize the discovery process and save the time and effort of users. In addition, the selection mechanism can be used to discover the useful static and dynamic context information to provide the most suitable and relative services for users.