RecommenderPlus: New Content-based User-centered Game Recommendation System
Tianrui Liu · 2022 3rd International Conference on Computer Vision, Image and Deep Learning & International Conference on Computer Engineering and Applications (CVIDL & ICCEA) · 2022
Many techniques have been incorporated into game recommendation systems, and they showed excellent accuracy in the recommendation. However, most of them are not user-centered, and users could only provide the game names to get their recommended list without any interaction. Therefore, we firstly conducted user research to evaluate what kind of factors will affect the games recommendation system. By analyzing the result of user research data, we concluded the influential factors our users genuinely care about. Then we designed a prototype/UI and deployed an application called RecommenderPlus, a user-centered steam games recommendation system based on the requirements of our users. Also, we introduced its design process and the challenges we met. After that, we analyzed and evaluated our model’s performance and discussed its advantages andlimits.