IMPORTANCE OF MACHINE LEARNING ALGORITHM IN INTELLECTUAL ANALYSIS OF WEB SITES

Abstract

In the digital age, where the Internet serves as a vast repository of information, the intelligent analysis of websites has become crucial for various applications ranging from user experience optimization to cybersecurity. This article explores the pivotal role of Machine Learning techniques in the analysis of web content, structure, and user interactions. By leveraging algorithms that can discern patterns, extract insights, and make predictions, Machine Learning enables the automated processing of vast amounts of web data, facilitating tasks such as content classification, sentiment analysis, anomaly detection, and personalized recommendation systems. Moreover, Machine Learning empowers web analysts to uncover hidden trends, detect malicious activities, and enhance the overall efficiency and effectiveness of website operations. Through a synthesis of case studies and theoretical frameworks, this article underscores the significance of integrating Machine Learning into web analysis workflows, highlighting its transformative impact on digital businesses, online security, and user engagement strategies.