Video Game Selection Recommendation System

This study aims to enhance the efficiency of the video game selection process for users through the implementation of advanced recommendation algorithms. The review the newest and most famous methods, means, algorithms and approaches to solving problems generation recommendations was done. Recommendation system was modeled with usage the UML diagram. Three algorithms have been implemented and analyzed the results of their work: collaborative ALS-based advisor, collaborative recommender systems utilizing EM and SVD, and content-driven recommenders. Collaborative ALS consultant showed itself the best. Developed information system can significantly improve users playing experience and make process of games selection more personalized and effective.