Eurasian Journal of Mathematical Theory and Computer Sciences 5-jild 6-son (2025) · 46–53-betlar

AI-DRIVEN UX OPTIMIZATION FOR WEB APPLICATIONS

Shoyqulov, Shodmonkul

DOI: 10.5281/zenodo.15755881 · Manbada o'qish → · PDF (manba serverida)

Annotatsiya

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.

Artificial intelligence, UX design, user interface, usability, web analytics, interaction data, machine learning, web application optimization.

Metadata manbasi: jurnal OAI-PMH arxivi · Sindex to'liq matnni saqlamaydi, manbaga havola beradi.