| Reference: | [1] A. Canossa, J. B. Martinez, and J. Togelius, Give me a reason to dig Minecraft and psychology of motivation. IEEE Conference on Computational Intelligence in Games, 2013.
[2] H. Cole and M. D. Griffiths, Social interactions in massively multiplayer online role-playing gamers. CyberPsychology & Behavior, 10(4), 575-583, 2007.
[3] K. Conley and D. Perry, How does he saw me? A recommendation engine for picking heroes in Dota 2. Project Report, CS229 Maching Learning Course, Stanford University, 2013.
[4] A. Drachen and A. Canossa, Evaluating motion: Spatial user behaviour in virtual environments. International Journal of Arts and Technology, 4(3), 294-314, 2011.
[5] A. Drachen, R. Sifa, C. Bauckhage, and C. Thurau, Guns, swords and data: Clustering of player behavior in computer games in the wild. IEEE Conference on Computational Intelligence and Games, 2012.
[6] A. Drachen, C. Thurau, R. Sifa, and C. Bauckhage, A comparison of methods for player clustering via behavioral telemetry. International Conference on the Foundations of Digital Games, 2013.
[7] A. Drachen, M. Yancey, J. Maguire, D. Chu, I. Y. Wang, T. Mahlmann, M. Schubert, and D. Klabajan, Skill-based differences in spatio-temporal team behaviour in defence of the ancients 2 (dota 2). IEEE Conference on Games media entertainment, 2014.
[8] Z. Fang, X. Zhou, J. Tang, W. Shao, A. C. M. Fong, L. Sun, Y. Ding, L. Zhou, and J. Luo, Modeling paying behavior in game social networks. ACM Conference on Information and Knowledge Management, 2014.
[9] L. Guo, J. Shao, K. L. Tan, and Y. Yang, Wheretogo: Personalized travel recommendation for individuals and groups. International Conference on Mobile Data Management, 2014.
[10] F. Johansson and J. Wikström, Result prediction by mining replays in Dota 2. Master Thesis, Department of Computer Science and Engineering, Faculty of Computing, Blekinge Institute of Technology, 2015
[11] S. Köhler, S. Bauer, D. Horn, and P. N. Robinson, Walking the interactome for prioritization of candidate disease genes. The American Journal of Human Genetics, 82(4), 949-958, 2008.
[12] J. H. Kim, D. V. Gunn, E. Schuh, B. Phillips, R. J. Pagulayan, and D. Wixon, Tracking real-time user experience (TRUE): a comprehensive instrumentation solution for complex systems. SIGCHI conference on Human Factors in Computing Systems, 2008.
[13] S. Müller, S. Frey, M. Kapadia, S. Klinger, R. P. Mann, B. Solenthaler, R. W. Sumner, and M. Gross, HEAPCRAFT: Quantifying and predicting collaboration in Minecraft. AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 2015.
[14] S. Müller, M. Kapadia, S. Frey, S. Klinger, R. P. Mann, B. Solenthaler, R. W. Sumner, and M. Gross, Statistical analysis of player behavior in Minecraft. IEEE Conference on the Foundations of Digital Games, 2015.
[15] T. Mahlmann, A. Drachen, J. Togelius, A. Canossa, and G. N. Yannakakis, Predicting player behavior in Tomb raider: Underworld. IEEE Symposium on Computational Intelligence and Games, 2010.
[16] D. Moura, M. S. El-Nasr, and C. D. Shaw, Visualizing and understanding players` behavior in video games: discovering patterns and supporting aggregation and comparison. ACM SIGGRAPH 2011 Game Papers, 2011.
[17] T. Nuangjumnonga and H. Mitomo, Leadership development through online gaming. 19th ITS Biennial Conference, Bangkok 2012: Moving Forward with Future Technologies-Opening a Platform for All, 2012.
[18] H. Y. Ong, S. Deolalikar, and M. Peng, Player behavior and optimal team composition for online multiplayer games. Project Report, CS229 Maching Learning Course, Stanford University, 2015.
[19] N. Pobiedina, J. Neidhardt, M. D. C. Calatrava Moreno, and H. Werthner, Ranking factors of team success. International Conference on World Wide Web, 2013.
[20] F. Rioult, J.-P. Métivier, B. Helleu, N. Scelles, and C. Durand, Mining tracks of competitive video games. AASRI Procedia, 8, 82-87, 2014.
[21] A. Semenov, P. Romov, S. Korolev, D. Yashkov, and K. Neklyudov, Performance of machine learning algorithms in predicting game outcome from drafts in Dota 2. International Conference on Analysis of Images, Social Networks and Texts, 2016.
[22] K. J. Shim and J. Srivastava, Team performance prediction in massively multiplayer online role-playing games (MMORPGs). IEEE Conference on Social Computing, 2010.
[23] R. Sifaa, A. Drachen, and C. Bauckhage, Profiling in games: Understanding behavior from telemetry. In Social Interaction in Virtual Worlds, Cambridge University Press, 2017.
[24] K. Song, T. Zhang, and C. Ma, Predicting the winning side of DotA2. Project Report ,CS229 Maching Learning Course, Stanford University, 2015.
[25] H. Tong, C. Faloutsos, and J.-Y. Pan, Fast random walk with restart and its applications. IEEE International Conference on Data Mining, 2006.
[26] H. Wang, B. Xia, and Z. Chen, Cultural difference on team performance between chinese and americans in multiplayer online battle arena games. International Conference on Cross-Cultural Design, 2015.
[27] B. G. Weber and M. Mateas, A data mining approach to strategy prediction. IEEE Symposium on Computational Intelligence and Games, 2009.
[28] P. Yang, B. E. Harrison, and D. L. Roberts, Identifying patterns in combat that are predictive of success in MOBA games. International Conference on the Foundations of Digital Games, 2014.
[29] N. Yee, Motivations for play in online games. CyberPsychology & Behavior, 9(6), 772-775, 2006.
[30] 邱楚翔, 《團隊表現績效預測：以NBA籃球運動為例》, 國立政治大學資訊科學系碩士論文, 2014. |
