Abstract
With the continuous development of e-sports, the application of data analysis in e-sports has been widely concerned. In this paper, we introduce the important process before the MOBA e-sports game: the bans and picks (BP). In order to solve the problem, we propose the improved meta-learning network structure. Our model uses Bi-LSTM as the controller to increase the link between past and future sequences. The modified cosine measure is used to replace the cosine measure to make the similarity determination more accurate. The simulation results show that the proposed structure has achieved good results in the e-sports BP prediction problem, and the accuracy rate is about 84%.
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Acknowledgment
This article is funded by the Jinling Institute of Science and Technology, a high-level talent research startup fund, and a web user behavior analysis and research project based on quantum algorithms (No. jit-b-201624).
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Yu, C., Zhu, Wn., Sun, Ym. (2019). E-Sports Ban/Pick Prediction Based on Bi-LSTM Meta Learning Network. In: Sun, X., Pan, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2019. Lecture Notes in Computer Science(), vol 11632. Springer, Cham. https://doi.org/10.1007/978-3-030-24274-9_9
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DOI: https://doi.org/10.1007/978-3-030-24274-9_9
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