Оптимізація 3D-моделей для використання у комп’ютерних іграх та інтерактивних середовищах

Abstract

The paper examines the use of neural networks in the analysis of website user experience (UX). Modern UX research often involves large volumes of textual data from user feedback, which can be difficult to process manually. In this study, a dataset of 40 user comments related to website navigation was generated using the open-source language model Mistral. The collected responses were then analyzed with a GPT-based language model capable of semantic grouping and summarization. The results demonstrate that neural network models significantly reduce the time required for data processing while preserving the logical structure of the findings. The study highlights the potential of integrating artificial intelligence tools into UX research and web interface design