This paper outlines a representation of knowledge based on semantic networks and organized in terms of semantic axes and "scenarios". A context mechanism for such nets is also discussed, along with an algorithm for integrating new information to a semantic net. Finally, an example is given to illustrate the representation and the context mechanism. 0. Introduction The representation of knowledg...

the internet is already the primary source of tourist destination information for travelers. according to world tourism organization, about 95% of web users use the internet to gather travel related information and about 93% indicate that they visited tourism web sites when planning for vacations. the number of people turning to the internet for vacation and travel planning has increased more t...

We present a novel fine-grained semantic representation of text and an approach to constructing it. This representation is largely extractable by today’s technologies and facilitates more detailed semantic analysis. We discuss the requirements driving the representation, suggest how it might be of value in the automated tutoring domain, and provide evidence of its validity.

A survey of research on spoken language understanding is presented. It covers aspects of knowledge representation, automatic interpretation strategies, semantic grammars, conceptual language models, semantic event detection, shallow semantic parsing, semantic classification, semantic confidence, active learning

To solve the problem of semantic loss in text representation, this paper proposes a new embedding method word representation space called wt2svec based on supervised latent Dirichlet allocation (SLDA) and Word2vec. It generates global topic vector utilizing SLDA which can discover information through topics whole document set. gets local The is obtained by combining with information. Additional...

A semantic network is a graph which represents semantic relations between concepts, used in a lot of fields as a form of knowledge representation. This paper describes an automatic approach to identify semantic relations between concepts by using statistical information extracted from the Web. We automatically constructed an associative network starting from a lexicon. Moreover we applied these...