Design representation is a common task in the design process to facilitate learning, analysis, redesign, communication, and other activities. Traditional techniques rely on human expertize manual construction are difficult repeat scale. Here, we present methodology that utilizes readily available large-scale multidisciplinary knowledge base (KB) automatically generate as semantic network, i.e.,...

An essential aim in the research on semantic cognition is to understand interplay between structure of representation and controlled processes that operate it generate flexible behaviours. To evaluate link network connectivity control functions (semantic inhibition switching), we employed a theory approach revealed processing was reliably associated with conceptual representation. In particular...

Vector space models have been successfully used for lexical semantic representation. Some of these models rely on distributional properties of words in large corpora, and have been contrasted with human performance on semantic similarity and priming in lexical decision tasks. Neural network models of lexical representation have been classically of reduced size due to computational limitations. ...

Semantic networks inspired by semantic information processing by the brain frequently do not improve the results of text classification. This counterintuitive fact is explained here by the multiple inheritance problem, which corrupts real-world knowledge representation attempts. After a review of early work on the use of semantic networks in text classification, our own heuristic solution to th...

Semantic Link Network SLN is a model of future Semantic Web and Knowledge Web. Based on our previous SLN model, this paper enriches the semantic links and reasoning rules, proposes a computing model for SLN, and develops relevant reasoning and managing mechanisms using a semantic matrix representation of SLN.

Semantic Link Network SLN is a semantic extension of hyperlink network. Based on the previous SLN model, this paper enriches the semantic links and reasoning rules, proposes an algebra model that supports semantic reasoning and the management of SLN by using a semantic matrix and presents the experiment for putting an SLN into practice. A solution to efficiently manage a huge SLN by dividing th...

In this article we present a neural network model of sentence generation. The network has both technical and conceptual innovations. Its main technical novelty is in its semantic representations: the messages which form the input to the network are structured as sequences, so that message elements are delivered to the network one at a time. Rather than learning to linearise a static semantic re...

This paper investigates an effective method of building domain-independent text generation system. In our English text generation system, Semantic Network is used as the internal Knowledge Representation. Nodes and links of the semantic network are classified according to word class and grammatical relations respectively. Generation results prove that the system works well and can generate cohe...