AI-DRIVEN UX OPTIMIZATION FOR WEB APPLICATIONS

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Выпуск: Том 5 № 6 : Евразийский журнал математической теории и компьютерных наук
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Associate Professor, department of Applied Mathematics, Karshi State university, Republic of Uzbekistan
info@in-academy.uz

Аннотация:

This paper explores how artificial intelligence (AI) can be applied to enhance user interface (UI) and user experience (UX) design in web applications. By analyzing real-time user interaction data such as mouse movements, click patterns, and session time, machine learning models identify usability issues and recommend interface improvements. The study compares traditional heuristic evaluation with AI-driven approaches and demonstrates how data-informed UX redesigns significantly improve engagement metrics. Experimental results suggest that AI integration leads to reduced bounce rates and more efficient user navigation, validating its role in next-generation UX design workflows.

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Как цитировать:

Shoyqulov, S. . (2025). AI-DRIVEN UX OPTIMIZATION FOR WEB APPLICATIONS. Евразийский журнал математической теории и компьютерных наук, 5(6), 46–53. извлечено от https://www.in-academy.uz/index.php/EJMTCS/article/view/56600

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