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A Mapping Approach to Identify Player Types for Game Recommendations

Department of Computer Engineering, Kumoh National Institute of Technology, 61 Daehak-ro, Gumi-si 39177, Korea
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Information 2019, 10(12), 379; https://doi.org/10.3390/info10120379
Received: 23 October 2019 / Revised: 19 November 2019 / Accepted: 28 November 2019 / Published: 2 December 2019
(This article belongs to the Special Issue Advances in Knowledge Graph and Data Science)
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.
Keywords: game; recommendation system; personality diagnosis; types of gamers game; recommendation system; personality diagnosis; types of gamers
MDPI and ACS Style

Lee, Y.; Jung, Y. A Mapping Approach to Identify Player Types for Game Recommendations. Information 2019, 10, 379.

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