A Mapping Approach to Identify Player Types for Game Recommendations

As the size of the domestic and international gaming industry gradually grows, various games are undergoing rapid development cycles to compete in the current market. However, selecting and recommending suitable games for users continues to be a challenging problem. Although game recommendation systems based on the prior gaming experience of users exist, they are limited owing to the cold start problem. Unlike existing approaches, the current study addressed existing problems by identifying the personality of the user through a personality diagnostic test and mapping the personality to the player type. In addition, an Android app-based prototype was developed that recommends games by mapping tag information about the user's personality and the game. A set of user experiments were conducted to verify the feasibility of the proposed mapping model and the recommendation prototype.