scholarly journals Development of domain thesaurus as a set of ontology concepts with use of semantic similarity and elements of combinatorial optimization

2021 ◽  
pp. 003-015
Author(s):  
Y.V. Rogushina ◽  
◽  
A.Y. Gladun ◽  

We consider use of ontological background knowledge in intelligent information systems and analyze directions of their reduction in compliance with specifics of particular user task. Such reduction is aimed at simplification of knowledge processing without loss of significant information. We propose methods of generation of task thesauri based on domain ontology that contain such subset of ontological concepts and relations that can be used in task solving. Combinatorial optimization is used for minimization of task thesaurus. In this approach, semantic similarity estimates are used for determination of concept significance for user task. Some practical examples of optimized thesauri application for semantic retrieval and competence analysis demonstrate efficiency of proposed approach.

Author(s):  
Wai-Tat Fu ◽  
Jessie Chin ◽  
Q. Vera Liao

Cognitive science is a science of intelligent systems. This chapter proposes that cognitive science can provide useful perspectives for research on technology-mediated human-information interaction (HII) when HII is cast as emergent behaviour of a coupled intelligent system. It starts with a review of a few foundational concepts related to cognitive computations and how they can be applied to understand the nature of HII. It discusses several important properties of a coupled cognitive system and their implication to designs of information systems. Finally, it covers how levels of abstraction have been useful for cognitive science, and how these levels can inform design of intelligent information systems that are more compatible with human cognitive computations.


2002 ◽  
Vol 8 (2-3) ◽  
pp. 93-96
Author(s):  
AFZAL BALLIM ◽  
VINCENZO PALLOTTA

The automated analysis of natural language data has become a central issue in the design of intelligent information systems. Processing unconstrained natural language data is still considered as an AI-hard task. However, various analysis techniques have been proposed to address specific aspects of natural language. In particular, recent interest has been focused on providing approximate analysis techniques, assuming that when perfect analysis is not possible, partial results may be still very useful.


2017 ◽  
Vol 21 (6) ◽  
pp. 1039-1040
Author(s):  
Quan Z. Sheng ◽  
Wei Emma Zhang ◽  
Elhadi Shakshuki

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