• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.217-218
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• 2021

본 논문에서는 다층 퍼셉트론을 활용하여 League of Legends 게임의 승패를 예측하는 Deep Neural Network 프로그램을 설계하는 방법을 제안한다. 연구 방법으로 한국 서버의 챌린저 리그에서 행해진 약 26000 경기 데이터 셋을 분석하여, 경기 도중 15분 데이터 중 드래곤 처치 수, 챔피언 레벨, 정령, 타워 처치 수가 게임 결과에 유의미한 영향을 끼치는 것을 확인하였다. 모델 설계는 softmax 함수보다 sigmoid 함수를 사용했을 때 더 높은 정확도를 얻을 수 있었다. 실제 LOL의 프로 게임 16경기를 예측한 결과 93.75%의 정확도를 도출했다. 게임 평균시간이 34분인 것을 고려하였을 때, 게임 중반 정도에 게임의 승패를 예측할 수 있음이 증명되었다. 본 논문에서 설계한 이 프로그램은 전 세계 E-sports 프로리그의 승패예측과 프로팀의 유용한 훈련지표로 활용 가능하다고 사료된다.

• Journal of Korea Multimedia Society
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• v.23 no.12
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• pp.1565-1575
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• 2020

This study examines the game balance of the MOBA game genre, which was selected as a model item for the Asian Games. The "bird-eye view" was used for a more efficient representation of 3D modeling. Based on that, statistical analysis was conducted to present appropriate game camera settings and camera balance to match the competitive structure of the MOBA game. A review of the game camera settings reveals that 64° to 70° is the angle that minimizes the difference in vision between the two-player teams the most. Through a one-way ANOVA analysis, we found that the user ranking level and SVB value are closely related. Therefore, the factor of the regression equation using the SVB value must have a user ranking level. As a result of the optimized camera focus analysis of , the camera setting methods were classified into 3 types. For main action games, the recommended camera angle is 64°~66°, and the recommended camera focus is 11.2 mm~19.3 mm. For action and strategy games, the camera angle is 66°~68°, camera focus - 19.3 mm~27.3 mm. And lastly, for the main strategy game, the recommended camera angle is 68°~70°, and the camera focus is 27.3 mm~35.3 mm.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.2
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• pp.61-68
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• 2020

E-sports has grown steadily in recent years and has become a popular sport in the world. In this paper, we propose a win-loss prediction model of League of Legends at the start of the game. In League of Legends, the combination of a champion statistics of the team that is made through each player's selection affects the win-loss of the game. The proposed model is a deep learning model based on Bidirectional LSTM embedding which considers a combination of champion statistics for each team without any domain knowledge. Compared with other prediction models, the highest prediction accuracy of 58.07% was evaluated in the proposed model considering a combination of champion statistics for each team.

• Journal of Korea Game Society
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• v.21 no.3
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• pp.117-132
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• 2021

This paper investigates how information game users needs to play game is offered to game user by applying the notion of explicitation toward translated game texts. By using League of Legends' Character lines, Character Abilities and Equipment Description texts as a case, this paper focused on how 'Insertion(addition)' and 'Replacement' method are applied toward game translation and which information is being explicitated. As a result, this paper found out that translation on Player vs. Player genre game, explicitation occurs by adding or replacing words containing information needed, and information about game control was prioritized among other information related with game universe and culture.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.213-221
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• 2021

In this paper, we suggest the Deep Neural Network Model System for predicting results of the match of 'League of Legends (LOL).' The model utilized approximately 26,000 matches of the LOL game and Keras of Tensorflow. It performed an accuracy of 93.75% without overfitting disadvantage in predicting the '2020 League of Legends Worlds Championship' utilizing the real data in the middle of the game. It employed functions of Sigmoid, Relu and Logcosh, for better performance. The experiments found that the four variables largely affected the accuracy of predicting the match --- 'Dragon Gap', 'Level Gap', 'Blue Rift Heralds', and 'Tower Kills Gap,' and ordinary users can also use the model to help develop game strategies by focusing on four elements. Furthermore, the model can be applied to predicting the match of E-sports professional leagues around the world and to the useful training indicators for professional teams, contributing to vitalization of E-sports.

• Journal of Korea Game Society
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• v.21 no.5
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• pp.133-142
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• 2021

This study investigated the effectiveness of 'League of Legends (LoL) game school', an e-sports online training program for relieving youth game over-flow. The Seoul Metropolitan Office of Education's Student Education Institute ran the program. Through this study, it was found that various activities to learn an e-sports game professionally and to explore career paths regarding game had positive effects on students' affections and intrinsic motivation. This study may contribute to helping youth as generation Z understand a healthy game culture.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.461-462
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• 2021

본 논문에서는 봇 프레임워크의 Dialog와 HeroCard를 활용하여 게임 리그 오브 레전드의 초보자를 가이드 해 줄 수 있는 챗봇을 설계하고 구현한다. 이 애플리케이션은 게임 리그 오브 레전드 플레이어의 성향에 맞는 게임 속 캐릭터를 추천해 줄 수 있고 게임 내 요소에 대한 소개 및 설명을 할 수 있다.

• Journal of Korea Game Society
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• v.15 no.1
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• pp.185-198
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• 2015

The purpose of this study is to analyze representation of characters of AOS online-game in order to find out the meanings of ontological game characters. This study selects characters of on-line game to analyze representations of game characters by Pierre L$\acute{e}$vy's ontological theory. The characters which represented in on-line games reproduced by costume play in off-line world reflect human desire and construct human existence. Online game character is an existing substance, which could expand human experiences by crossing virtual game world and reality in digital era.

• Journal of Korea Game Society
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• v.15 no.1
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• pp.35-44
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• 2015

The purpose of this study is to analyze user-generated rules in online games and to define the way of players' identities are developed. This study focuses on the online game League of Legends, which originated from use map system. Based on rule theory, this study analyzes the characteristics of user-generated rules. As the result, this study proves that the main rule of online game is not the rules made by developers, but the emergent rules made by players. Through rule-detection and rule-selection process, user-generated rules change the game system. Therefore, the result of this study expects to show meaningful roles of players in game system.

• Journal of Korea Game Society
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• v.14 no.5
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• pp.147-160
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• 2014

The purpose of this study is to analyze figurations of genders in on-line game character in order to find out the ways of building gender identity of on-line game characters. This study selects characters in on-line game to analyze figurations of genders in game systems, images, discourses of game characters by using gender identity theory and examine the reproducing process of players. As the result, the gender identity of on-line game characters which was pre-given by game developers follows the same conventions and stereotypes in real world and also the players follow it in the same manner. On-line game has the potential of text involvement and modification of the game players, and it has immanent possibilities of becoming alternative space of endless improvement and evolvement.