Prototype of a content-based web page classification system using deep neural networks

The quality of the web page classification process has a huge impact on information retrieval systems. In this article, a solution is proposed that combines the results of classifiers of text and graphic data in order to obtain an accurate representation of web pages. The process of classifying graphical and textual data was implemented using deep learning models. The classification system can be used both to recommend content and to filter unwanted information.