A novel architecture of semantic web reasoner based on transferable belief model

C. Pantoja, E. Izquierdo
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Abstract

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.
一种基于可转移信念模型的语义web推理器结构
随着语义Web的普及,对不精确和不确定的信息进行表示和推理的技术挑战仍然是一个突出的问题。语义网的基础是实体之间关系的断言,但这些关系通常没有程度或级别的关系。使用一个简单的主语-谓语-宾语三元组,我们可以说“Alice”(主语)“喜欢”(谓语)“摇滚音乐”(宾语),但我们不能以80%的置信度或水平说她这样做。我们建议使用可转移信念模型(TBM)作为实现这一目标的一种方法。在这项工作中提出了两个贡献:一个以与TBM一致的方式表示信息的本体,以及一个评估给定系统知识的推理器。测试表明该模型在大规模语义网信息上的应用是可行的,但还需要进一步的优化和测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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