Sistema de recomendación para productos ecnológicos utilizando web scraping para la toma de decisiones en compra

Abstract

The growing number of online stores and the abundance of information about technology products make it difficult for consumers to make purchasing decisions. Browsing multiple websites to compare options has become a complex and overwhelming process. This can lead to hasty decisions or the purchase of products that do not meet expectations, and even, in many cases, to the final abandonment of the purchase. The technology product recommendation system offers functionalities such as product visualization, generation of recommendations, visualization of product details and the option to add products to a list of favorites. For the development of the progressive web application (PWA) and its graphical interfaces, React.js was used. In addition, the Flask framework was used to implement the REST API services, while MongoDB was used as the database manager, ensuring efficient and structured information management. The results obtained from the evaluation of the recommendation system were positive. There was a notable decrease in the time required to search and make purchasing decisions. These results validate the effectiveness of the system in optimizing purchasing decisions.