Collaborative and Content Based Recommendation for Game Recommender System

Recommender systems improve the access to relevant information and products by giving suggestions to the user based on user’s previous rating to the product or like and dislike of user towards the information. Many existing recommendation system use collaborative filtering approach that give recommendation based on other users preferences. On the other side we have content based method which gives recommendation based on user’s previous history or past profile. Game Recommender System aims to provide accurate results of recommendation to the user by both the available approaches. The system maintains user profile with certain ratings given to the games and based on that recommendation results are displayed to the user. The system has great advantage as it has personalized recommendation with social filtering methods to accurately recommend games to the user, so user can enjoy games that matches their interest and helps user to remove confusion as to which game they should play with plenty of games available in the market.