상세정보
학술대회
Champion Recommendation System of League of Legends
- 발행일
- 202010
- 출처
- International Conference on Information and Communication Technology Convergence (ICTC) 2020, pp.1252-1254
- 협약과제
- 20IH3300, 메타 플레이 인식 기반 지능형 게임 서비스 플랫폼 개발, 양성일
- 초록
- The multiplayer online battle arena (MOBA) game genre is one of the most popular game genres in the world. One of the MOBA games, League of Legends (LoL), is popular with game players, and professional leagues have been created worldwide. LoL has the ban and pick system to ban or pick champions before the game starts. This system affects the outcome of the game, which is even more important in the professional leagues. In this paper, we present a champion recommendation system of LoL. Recommendations are conducted sequentially in the same manner as in the ban and pick system. To address this challenge, we collect professional matches to create the ban and pick dataset and use the data to train two models for both teams. Experimental results show that the neural network classifier performs better than the random forest classifier. In addition, we explain the reason that the performances of the two models are different by separately analyzing the sequences.
- KSP 제안 키워드
- League of legends, Multiplayer online battle arena, Neural network Classifiers, Recommendation System, game genres, random forest classifier