System of methodological and instrumental tools for automated analysis of UX research data using artificial intelligence systems
DOI:
https://doi.org/10.26906/SUNZ.2025.1.96-106Keywords:
UX research, automation, data analysis, neural networks, expert systems, web-interfaceAbstract
The article is dedicated to the automated analysis of user experience (UX) research results using artificial intelligence systems, particularly neural networks and expert systems. The aim of the research is to develop a system of methodological
and instrumental tools for automating UX research data analysis through the integration of artificial intelligence technologies and
expert systems. The relevance of automating the processing of large volumes of heterogeneous data obtained from user interaction
research with digital products has been analyzed. A classification of user interaction research methods and digital products by data
types and an approach to selecting appropriate neural network architectures for their analysis are proposed. The possibilities of
using recurrent and convolutional neural networks as examples for processing text, audio, and video data are examined. The use of
an expert system for automated selection of neural networks optimal for analyzing various types of data is also proposed. A trial
version of the system using artificial intelligence API has been developed and tested, confirming the possibility of automated
processing of various types of UX research data using neural networks. Prospects for further development of the UX research data
analysis system are outlined, including software development, functionality expansion, and adaptation for related fields. The research results have practical significance for improving the efficiency of data analysis and can be used to enhance the interface
design process.
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