知识表示(knowledge representation)是指把知识客体中的知识因子与知识关联起来,便于人们识别和理解知识。知识表示是知识组织的前提和基础,任何知识组织方法都是要建立在知识表示的基础上。知识表示有主观知识表示和客观知识表示两种。

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简介: 计算机视觉研究大多都集中在不重叠的目标对象上,然而,目标对象却不足以描述丰富的视觉知识,于是,研究者就通过语言特征来获取更多的信息。通过图片与文字叙述相结合的多模态信息融合来获取一个场景图谱。

场景要旨的吸引人的想法的困难在于,关于“要旨”的内容尚无共识。 场景中某些对象应至少是要点的一部分。必须将对象之间的某些关系编码为要点。 即使将所有物体都相同,所要表达的含义却不同。

图表示学习无处不在:

对具有独立对象和关系的特征进行学习,将获得一个场景图谱:

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最新论文

We present an overview on Temporal Logic Programming under the perspective of its application for Knowledge Representation and declarative problem solving. Such programs are the result of combining usual rules with temporal modal operators, as in Linear-time Temporal Logic (LTL). We focus on recent results of the non-monotonic formalism called Temporal Equilibrium Logic (TEL) that is defined for the full syntax of LTL, but performs a model selection criterion based on Equilibrium Logic, a well known logical characterization of Answer Set Programming (ASP). We obtain a proper extension of the stable models semantics for the general case of arbitrary temporal formulas. We recall the basic definitions for TEL and its monotonic basis, the temporal logic of Here-and-There (THT), and study the differences between infinite and finite traces. We also provide other useful results, such as the translation into other formalisms like Quantified Equilibrium Logic or Second-order LTL, and some techniques for computing temporal stable models based on automata. In a second part, we focus on practical aspects, defining a syntactic fragment called temporal logic programs closer to ASP, and explain how this has been exploited in the construction of the solver TELINGO.

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