Back to Search Start Over

Design of AI System for National Fitness Sports Competition Action Based on Association Rules Algorithm.

Authors :
Xiang, Jianmin
Tong, Litao
Zhou, Shengfa
Source :
Computational Intelligence & Neuroscience. 9/16/2022, p1-11. 11p.
Publication Year :
2022

Abstract

In information system construction, online data migration is a very important link. At present, in different fields, people provide protection for online data migration through the way of project management to ensure the speed and efficiency of online migration. However, some problems may occur in the process of online data migration. In the development of contemporary sports, competitive sports, as the high-end stage of sports development, are constantly pursued by ordinary sports enthusiasts. Therefore, in the national fitness activities, how to combine the national fitness and competitive sports data to provide a more professional storage platform is a focus of research but also a problem to be solved in the process of online data migration. Because the data mining ID3 algorithm only supports querying and retrieving RowKey indexes, it does not support non-RowKey column indexing. Therefore, if you want to query non-RowKey indexes, the data mining ID3 algorithm will search the form in the overall scan, but the performance of this method is low. In order to improve the query speed of non-RowKey columns, this paper designs a secondary index function based on HBase. The sports competition action system can retrieve data from the secondary index of the query state, to avoid scanning the whole world and improve the search speed. In this paper, ID3 algorithm is used to combine national fitness and competitive sports data, which provides a guarantee for the migration of competitive sports data in the national fitness system. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16875265
Database :
Academic Search Index
Journal :
Computational Intelligence & Neuroscience
Publication Type :
Academic Journal
Accession number :
159173147
Full Text :
https://doi.org/10.1155/2022/1375009