There exists an injective, information-preserving function that maps a semantic network (i.e a directed labeled network) to a directed network (i.e. a directed unlabeled network). The edge label in the semantic network is represented as a topological feature of the directed network. Also, there exists an injective function that maps a directed network to an undirected network (i.e. an undirecte...

Objectives. We investigate several visual approaches for exploring semantic groups, a grouping of semantic types from the Unified Medical Language System (UMLS) semantic network. We are particularly interested in the semantic coherence of the groups, and we use the semantic relationships as important indicators of that coherence. Methods. First, we create a radial representation of the number o...

Semantic Networks (SN) are a knowledge representation paradigm especially suited for the meaning representation of natural language expressions. In order to clearly define their basic constructs, the relations and functions used in a semantic network must be given a logical characterization. The paper exemplifies this strategy for Multilayered Extended Semantic Networks (the so-called MultiNet ...

The paper describes a question answering system for German called InSicht. All documents in the system are analyzed by a syntactico-semantic parser in order to represent each document sentence by a semantic network (in the MultiNet formalism) or a partial semantic network (if only a parse in chunk mode succeeds). A question sent to InSicht is parsed yielding its semantic network representation ...

This paper introduces a semantic representation for virtual prototyping in interactive virtual construction applications. The representation reflects semantic information about dynamic constraints to define objects’ modification and construction behavior as well as knowledge structures supporting multimodal interaction utilizing speech and gesture. It is conveniently defined using XML-based mar...

in this paper, a state-of-the-art neuron mathematical model of neural tensor network (ntn) is proposed to rdf knowledge base completion problem. one of the difficulties with the parameter of the network is that representation of its neuron mathematical model is not possible. for this reason, a new representation of this network is suggested that solves this difficulty. in the representation, th...

In this paper an integration approach is introduced that supports the interrelation of the distributed product model across tools boundaries using knowledge representation concepts like the Resource Description Framework (RDF). The product model stays “inside” the models of the used tools. This reduces the integration costs. The interrelated product model defines a network representing knowledg...

Semantic networks were developed in cognitive science and artificial intelligence studies as graphical knowledge representation and inference tools emulating human thought processes. Formal analysis of the representation and inference capabilities of the networks modeled them as subsets of standard first-order logic (FOL), restricted in the operations allowed in order to ensure the tractability...