This paper deals with the semantic representation of user utterances within development of computerized dialogue system intended for city information center. The formalisms for description of natural language are mentioned and verified on user utterances and first dialogue turns within selected domain areas. A parser analyzing the utterance segments according to given rules is presented. Then t...

The processing of semantic information requires the adequate knowledge representation and ability to interpret semantically related knowledge. The majority of present day approaches to knowledge representation and processing are based on symbolic approach, i.e. on describing the meaning of represented domain knowledge and procedural knowledge used to process this domain knowledge. Hierarchical ...

Semantic representation lies at the core of several applications in Natural Language Processing. However, most existing semantic representation techniques cannot be used effectively for the representation of individual word senses. We put forward a novel multilingual concept representation, called MUFFIN, which not only enables accurate representation of word senses in different languages, but ...

The Semantic Web initiative defines important challenges for knowledge representation and database systems. Recently, several standards for representation languages have been proposed (RDF, DAML+OIL, OWL). We briefly discuss the logical basis of these representation languages by referring to description logic (DL) inferences systems. By introducing the DL inference system Racer we demonstrate t...

Abstract An influential view in (philosophy of) cognitive science is that computation systems semantic, conceptually depending on representation: to compute manipulate representations. I argue accepting the non-semantic teleomechanistic of lays ground for a promising alternative strategy, which helps explain and naturalise representation, rather than other way around. show this computation-base...

Current neural machine translation (NMT) usually extracts a fixedlength semantic representation for source sentence, and then depends on this representation to generate corresponding target translation. In this paper, we proposed a pivot-based semantic splicing model (PBSSM) to obtain a semantic representation including more translation information for source sentence, thus improving the transl...

Recently, zero-shot learning (ZSL) has received increasing interest. The key idea underpinning existing ZSL approaches is to exploit knowledge transfer via an intermediate-level semantic representation which is assumed to be shared between the auxiliary/source dataset and the target/test dataset and re-used as a bridge between the source and target domains for knowledge transfer. The semantic r...