Recommendation system for planning an advertising campaign based on the analysis of web traffic data and user behavior

Abstract

This qualifying work considers a recommender system for planning an advertising campaign based on the analysis of web traffic data and user behavior. Existing advertising campaign planning systems were analyzed. The choice of the architecture of the recommender system was substantiated, then the technologies for implementing the system were considered. A model of a recommender system consisting of a server part, a client part and a database was developed. A recommender system for planning an advertising campaign and user behavior was implemented using the C# programming language, using ASP.NET, Angular and MySQL technologies.