Open AccessMachine Learning and Data mining on the innovation of E-sports industry
Author(s) -
Yiqing Chen,
Jie Mei,
Steward Huang
Publication year - 2020
Publication title -
international journal of education and information technologies
Language(s) - English
Resource type - Journals
ISSN - 2074-1316
DOI - 10.46300/9109.2020.14.15
Subject(s) - competitor analysis , big data , computer science , outcome (game theory) , enhanced data rates for gsm evolution , data science , artificial intelligence , specialty , engineering management , knowledge management , machine learning , engineering , marketing , data mining , business , psychology , mathematics , mathematical economics , psychiatry
AI technology brings many revolutionary innovation opportunities to the e-sports industry. With the help of data mining, we can analyze the advantages and disadvantages of competitors, and predict the trend of the situation in the future. With the help of the agent created by intensive in-depth learning, it can assist players of different levels to carry out routine training, so as to improve the overall activity of the game. With the help of AI's big data advantage, AI can assist E-sports teaching to regard E-sports specialty as an experimental platform for using cutting-edge technology to reform and innovate traditional education and provide forward-looking guidance for future education. This paper uses CNN, LSTM, and LSTM + CNN three model to predict the outcome of the game according to the heroes selected by both teams, and has achieved good prediction results.