Analysis of sports event data based on the LSTM

被引：0

作者：

Son, Qyanyu ^{[1
]}

Lu, Rong ^{[2
]}

机构：

[1] Guangdong Univ Sci & Technol, Sch Phys Educ, Res Ctr GDUST, Dept PE, Dongguan 523013, Peoples R China

[2] Dongguan Polytech, Coll Artificial Intelligence, Dongguan 523083, Peoples R China

来源：

PROCEEDINGS OF 2024 INTERNATIONAL CONFERENCE ON COMPUTER AND MULTIMEDIA TECHNOLOGY, ICCMT 2024 | 2024年

关键词：

sports events; data analysis; NLP; emotion analysis; LSTM;

D O I：

10.1145/3675249.3675348

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

This study uses long-term memory network (LSTM). By collecting and processing a large amount of historical event data, we have developed an LSTM model for predicting the results and trends of sports competitions, as well as public opinion. The model considers multiple factors including team performance, player data, game time, to improve prediction accuracy. The experimental results show that our model has significant effects in predicting the results of sports events, which provides new ideas and methods for the analysis of sports event data.

引用

下载

页码：564 / 568

页数：5

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