Research Article
Data Mining Algorithm Based on Fusion Computer Artificial Intelligence Technology
@ARTICLE{10.4108/eetsis.3779, author={Yingqian Bai and Kepeng Bao and Tao Xu}, title={Data Mining Algorithm Based on Fusion Computer Artificial Intelligence Technology}, journal={EAI Endorsed Transactions on Scalable Information Systems}, volume={10}, number={6}, publisher={EAI}, journal_a={SIS}, year={2023}, month={10}, keywords={Artificial intelligence, Data mining, Information entropy, Data schema tree, Neural network}, doi={10.4108/eetsis.3779} }- Yingqian Bai
Kepeng Bao
Tao Xu
Year: 2023
Data Mining Algorithm Based on Fusion Computer Artificial Intelligence Technology
SIS
EAI
DOI: 10.4108/eetsis.3779
Abstract
INTRODUCTION: The paper constructs a massive data mining model of distributed spatiotemporal databases for the Internet of Things. Then a homologous data fusion method based on information entropy is proposed. The storage space required by the tree structure is reduced by constructing the data schema tree of the merged data set. Secondly, the optimal dynamic support degree is obtained by using a neural network and genetic algorithm. Frequent items in the Internet of Things data are mined to achieve the normalization of the clustered feature data based on the threshold value. Experiments show that the F-measure of the data mining algorithm improves the efficiency by 15.64% and 18.25% compared with the kinds of other literatures respectively. RI increased by 21.17% and 26.07%, respectively.