A novel architecture of semantic web reasoner based on transferable belief model
As the Semantic Web gains popularity, the technical challenges of representing and reasoning with imprecise and uncertain information still remain an outstanding issue. The foundation of the Semantic Web is the assertion of relations between entities, but these relations usually do not carry a degree or level of relationship. Using a simple subject-predicate-object triple we can say that “Alice” (subject) “likes” (predicate) “Rock music” (object), but we can not say that she does so with a confidence or level of 80%. We propose the use of the Transferable Belief Model (TBM) as a way to achieve this. Two contributions are presented in this work: an ontology to represent information in a way which is consistent with the TBM, and a reasoner to assess the knowledge of a given system. Tests show the feasibility of applying this model on large scale Semantic Web information, but further optimisations and tests must be performed.