Ontology-Based Approach to Construction of Intelligent Interface for Inductive Modeling Tools

Павлов, А С; Pidnebesna, Halyna; Stepashko, Volodymyr

doi:10.1109/csit49958.2020.9322012

Cited by 3 publications

(1 citation statement)

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“…An important feature of the inductive approach implementation is the nature of the uncertainty in information data sets (probabilistic, interval, fuzzy), as this approach is based on methods of data analysis. In a number of works [28][29][30], the ontological approach for the construction of the mathematical models within the framework of the inductive approach is based on a group of methods of data handling (GMDH). Within the framework of the proposed approach, the key parameters for the main components of the modeling process are identified, which determine the possibility of generalization and expediency of constructing multifunctional software modules in the development of computer inductive modeling tools based on GMDH [26,31,32].…”

Section: Introductionmentioning

confidence: 99%

Ontology of Mathematical Modeling Based on Interval Data

et al. 2022

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An ontological approach as a tool for managing the processes of constructing mathematical models based on interval data and further use of these models for solving applied problems is proposed in this article. Mathematical models built using interval data analysis are quite effective in many applications, as they have “guaranteed” predictive properties, which are determined by the accuracy of experimental data. However, the application of mathematical modeling methods is complicated by the lack of software tools for the implementation of procedures for constructing this type of mathematical models, creating an ontological model that operates by the categories of the subject area of mathematical modeling, regardless of the modeling object proposed in this article. This approach has made it possible to generate tools for mathematical modeling of various objects based on the interval data analysis for any software development environment selected by the user. The technology of creating the software on the basis of the developed ontological superstructure for mathematical modeling using the interval data for different objects, as well as various forms of user interface implementation, is presented in this article. A number of schemes, which illustrate the technology of using the ontological approach of mathematical modeling based on interval data, are presented, and the features of its interpretation when solving environmental monitoring problems are described.

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Section: Introductionmentioning

confidence: 99%

Ontology of Mathematical Modeling Based on Interval Data

et al. 2022

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Evolutionary Method Based on Artificial Bee Colony and Ontological Approach for Structural Identification of Interval Discrete Models of Objects with Distributed Parameters

Dyvak

Melnyk

Martsenyuk

et al. 2022

2022 12th International Conference on Advanced Computer Information Technologies (ACIT)

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Intelligent User Interfaces and Their Evaluation: A Systematic Mapping Study

Brdnik

Heričko

Šumak

2022

Sensors

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Intelligent user interfaces (IUI) are driven by the goal of improvement in human–computer interaction (HCI), mainly improving user interfaces’ user experience (UX) or usability with the help of artificial intelligence. The main goal of this study is to find, assess, and synthesize existing state-of-the-art work in the field of IUI with an additional focus on the evaluation of IUI. This study analyzed 211 studies published in the field between 2012 and 2022. Studies are most frequently tied to HCI and SE domains. Definitions of IUI were observed, showing that adaptation, representation, and intelligence are key characteristics associated with IUIs, whereas adaptation, reasoning, and representation are the most commonly used verbs in their description. Evaluation of IUI is mainly conducted with experiments and questionnaires, though usability and UX are not considered together in evaluations. Most evaluations (81% of studies) reported partial or complete improvement in usability or UX. A shortage of evaluation tools, methods, and metrics, tailored for IUI, is noticed. Most often, empirical data collection methods and data sources in IUI evaluation studies are experiment, prototype development, and questionnaire.

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Ontology-Based Approach to Construction of Intelligent Interface for Inductive Modeling Tools

Cited by 3 publications

References 3 publications

Ontology of Mathematical Modeling Based on Interval Data

Ontology of Mathematical Modeling Based on Interval Data

Evolutionary Method Based on Artificial Bee Colony and Ontological Approach for Structural Identification of Interval Discrete Models of Objects with Distributed Parameters

Intelligent User Interfaces and Their Evaluation: A Systematic Mapping Study

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