International Journal of Scientific Research and Engineering Development

Modern web systems are becoming more interactive. But, most of the websites still provide the same experience to users without understanding their behaviour or interaction patterns. Adaptive web systems are more important than ever as users expect smarter, more personalised digital experiences. In this paper we discuss the potential of predictive behavioural intelligence to enhance modern web applications, through analysis of real-time user activities and dynamic adaptation of web interfaces according to user behaviour. The proposed framework emphasises on behavioural analytics techniques like click frequency, screen time, cursor movement, scroll depth and navigation patterns to understand user interests and interaction intent. Leveraging predictive intelligence and adaptive rendering mechanisms, the system can dynamically modify content visibility, recommendations, and interface structures to enhance user engagement and interaction efficiency. The framework also includes machine learning models, behavioural tracking systems and intelligent feedback mechanisms, to enable smarter and more responsive web environments. Furthermore, the proposed system supports continuous adaptive learning, which helps web applications to provide more personalised, efficient and user-friendly experiences in real time.

V.Udhayakumar, M.Manikandan,"Predictive Behavioral Intelligence Framework For Adaptive Web Systems" International Journal of Scientific Research and Engineering Development, V9(3): Page(1821-1826) May-June 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.