Simple Reasoning for Contextualized RDF Knowledge
Joseph Mathew, Luciano Serafini · Frontiers in artificial intelligence and applications · 2011
The standard semantic web languages and reasoning tools do not explicitly take into account the contextual dimension of knowledge, i.e., the fact that a certain statement (RDF triple) is not universally true, but true only in certain circumstances. Such contextual information, which includes for instance, the time interval, the spatial region, or the sub-domain in which a certain statement holds, are of foremost importance to determine correct answers for a user query. Rather than proposing a new standard, in this work, we introduce a framework for contextual knowledge representation and reasoning based on current RDF(S) standards, and we provide a sound and complete set of forward inference rules that support reasoning in and across contexts. The approach proposed in this paper has been implemented in a prototype, which will be briefly described.