A General Framework for Representing and Reasoning with Annotated Semantic Web Data.
In Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI-10), 2010.
Abstract:
We describe a generic framework for representing and reasoning with annotated Semantic Web data, a task becoming more important with the recent increased amount of inconsistent and non-reliable meta-data on the web. We formalise the annotated language, the corresponding deductive system and address the query answering problem. Our work extends previous contributions on RDF annotations by providing a unified reasoning formalism and allowing the seamless combination of different annotation domains. We show that current RDF stores can easily be extended to our framework. We demonstrate the feasibility of our method by instantiating it on (i) temporal RDF; (ii) fuzzy RDF; (iii) and their combination. A prototype shows that implementing and combining new domains is easy.