Розробка веб-сервісу рекомендацій на основі аналізу поведінкових даних користувачів

Abstract

In today's information society, web services that provide personalized information and recommendations have become essential and popular. With the advancement of data analysis and machine learning technologies, developing web recommendation services based on user behavior analysis is a relevant task in the field of information technology. This article discusses the development of a recommendation web service that analyzes user behavior data to provide personalized recommendations, aiming to enhance user experience and meet their individual needs. The problem statement emphasizes the need to develop a web service for recommendations based on user behavior analysis. The tasks involved in achieving this goal include data collection and processing, data analysis, development of a recommendation algorithm, and the creation of a user-friendly web interface. The main task of this project is to develop a web service for recommendations based on user behavior analysis. The service aims to improve the user experience and satisfy individual needs by providing personalized recommendations that consider user preferences, activities, and context. In conclusion, the development of a web service for recommendations based on user behavior analysis is an important and timely task in today's information society. Leveraging user behavior data and machine learning algorithms enables the improvement of user experience and the provision of personalized recommendations. Developing such a service involves data collection and processing, algorithm development, and the implementation of a user-friendly web interface. Further advancements in these services can enhance personalization and effectiveness in information retrieval for users.