Open AccessImproving the cognitive clarity of graph models of knowledge representation and decision-making using visualization
Author(s) -
Руслан Исаев,
Aleksandr Podvesovskiy
Publication year - 2021
Publication title -
èrgodizajn
Language(s) - English
Resource type - Journals
eISSN - 2658-4026
pISSN - 2619-1512
DOI - 10.30987/2658-4026-2021-1-27-35
Subject(s) - clarity , visualization , computer science , cognition , representation (politics) , graph , relevance (law) , artificial intelligence , cognitive science , human–computer interaction , theoretical computer science , psychology , biochemistry , chemistry , neuroscience , politics , political science , law
The article discusses the ways to improve the cognitive clarity of graph models for knowledge representation and decision making by applying visualization capabilities. Using fuzzy cognitive models as an example, it is shown that applying an approach based on visualization metaphors allows one to structure and partially formalize the task of increasing the cognitive clarity of models, breaking it down into separate easily interpreted stages, each of which contributes to providing cognitive clarity in general. The conclusion is made about the relevance of developing visualization metaphors to increase the cognitive clarity of graph models of other types.